-------------------------------------------------------------------------------
      name:  <unnamed>
       log:  /Users/bundi/Desktop/Self-Selection and Misreporting/Revision/Repl
> ication/Replication_Final/pep_session_replication.smcl
  log type:  smcl
 opened on:  15 Jul 2016, 14:27:55

. do "/Users/bundi/Desktop/Self-Selection and Misreporting/Revision/Replication
> /Replication_Final/PEP_Do_Replication.do"

. *Replication File for "Self-Selection and Misreporting in Legislative Surveys
> "
. 
. *Read data
. use "PEP_Replica_Final.dta", clear

. 
. *Self-Selection Bias (Table 1)
. tab survey int_count_d, row

+----------------+
| Key            |
|----------------|
|   frequency    |
| row percentage |
+----------------+

    survey |
participat |   validated evaluation demand
       ion |        no       once  several t |     Total
-----------+---------------------------------+----------
        no |        86         26         21 |       133 
           |     64.66      19.55      15.79 |    100.00 
-----------+---------------------------------+----------
       yes |        74         23         15 |       112 
           |     66.07      20.54      13.39 |    100.00 
-----------+---------------------------------+----------
     Total |       160         49         36 |       245 
           |     65.31      20.00      14.69 |    100.00 


. 
. *Misreporting Bias. Difference between Validated and Reported Data (Table 2)
. *Reported Data
. tab pr if survey==1 & pr==1 | survey==1 & pr==2 | survey==1 & pr==3

     parliamentary |
           request |      Freq.     Percent        Cum.
-------------------+-----------------------------------
                no |         43       44.33       44.33
     yes, one time |         22       22.68       67.01
yes, several times |         32       32.99      100.00
-------------------+-----------------------------------
             Total |         97      100.00

. *Validated Data
. tab int_count_d if survey==1 & pr==1 | survey==1 & pr==2 | survey==1 & pr==3

    validated |
   evaluation |
       demand |      Freq.     Percent        Cum.
--------------+-----------------------------------
           no |         66       68.04       68.04
         once |         18       18.56       86.60
several times |         13       13.40      100.00
--------------+-----------------------------------
        Total |         97      100.00

. 
. *Misreporting Bias. Overview of Over- and Underreporting (Table 3)
. tab pr int_count_d if survey==1 & pr==1 | survey==1 & pr==2 | survey==1 & pr=
> =3, cell

+-----------------+
| Key             |
|-----------------|
|    frequency    |
| cell percentage |
+-----------------+

     parliamentary |   validated evaluation demand
           request |        no       once  several t |     Total
-------------------+---------------------------------+----------
                no |        34          7          2 |        43 
                   |     35.05       7.22       2.06 |     44.33 
-------------------+---------------------------------+----------
     yes, one time |        15          3          4 |        22 
                   |     15.46       3.09       4.12 |     22.68 
-------------------+---------------------------------+----------
yes, several times |        17          8          7 |        32 
                   |     17.53       8.25       7.22 |     32.99 
-------------------+---------------------------------+----------
             Total |        66         18         13 |        97 
                   |     68.04      18.56      13.40 |    100.00 


. 
. *General Self-Selection bias (Table 4)
. *Invited to Survey
. *Party
. tab party_big

  party big |      Freq.     Percent        Cum.
------------+-----------------------------------
        SVP |         58       23.67       23.67
         SP |         57       23.27       46.94
        FDP |         41       16.73       63.67
        CVP |         42       17.14       80.82
      Other |         47       19.18      100.00
------------+-----------------------------------
      Total |        245      100.00

. *Sex
. tab sex

     gender |      Freq.     Percent        Cum.
------------+-----------------------------------
       male |        174       71.02       71.02
     female |         71       28.98      100.00
------------+-----------------------------------
      Total |        245      100.00

. *Language
. tab lang

   language |      Freq.     Percent        Cum.
------------+-----------------------------------
    deutsch |        177       72.24       72.24
franz�sisch |         57       23.27       95.51
italienisch |         11        4.49      100.00
------------+-----------------------------------
      Total |        245      100.00

. *Age
. tab age_categories

age_categor |
        ies |      Freq.     Percent        Cum.
------------+-----------------------------------
      35-49 |         62       25.31       25.31
      50-64 |        141       57.55       82.86
       < 35 |         15        6.12       88.98
       > 64 |         27       11.02      100.00
------------+-----------------------------------
      Total |        245      100.00

. *Seniority
. tab seniority_categories

  Seniority |
 Categories |      Freq.     Percent        Cum.
------------+-----------------------------------
        4-7 |         61       24.90       24.90
       8-11 |         44       17.96       42.86
        < 4 |         91       37.14       80.00
        >11 |         49       20.00      100.00
------------+-----------------------------------
      Total |        245      100.00

. *Committee
. tab committee_2010_2014

committee_2 |
   010_2014 |      Freq.     Percent        Cum.
------------+-----------------------------------
legislative |        152       62.04       62.04
  oversight |         93       37.96      100.00
------------+-----------------------------------
      Total |        245      100.00

. *Interventions
. tab interventions_categories

Interventio |
         ns |
 Categories |      Freq.     Percent        Cum.
------------+-----------------------------------
      10-19 |         65       26.53       26.53
      20-29 |         45       18.37       44.90
        <10 |         47       19.18       64.08
        >30 |         88       35.92      100.00
------------+-----------------------------------
      Total |        245      100.00

. 
. *Participated in the Survey
. *Party
. tab party_big if survey==1

  party big |      Freq.     Percent        Cum.
------------+-----------------------------------
        SVP |         21       18.75       18.75
         SP |         32       28.57       47.32
        FDP |         18       16.07       63.39
        CVP |         19       16.96       80.36
      Other |         22       19.64      100.00
------------+-----------------------------------
      Total |        112      100.00

. *Sex
. tab sex if survey==1

     gender |      Freq.     Percent        Cum.
------------+-----------------------------------
       male |         74       66.07       66.07
     female |         38       33.93      100.00
------------+-----------------------------------
      Total |        112      100.00

. *Language
. tab lang if survey==1

   language |      Freq.     Percent        Cum.
------------+-----------------------------------
    deutsch |         77       68.75       68.75
franz�sisch |         28       25.00       93.75
italienisch |          7        6.25      100.00
------------+-----------------------------------
      Total |        112      100.00

. *Age
. tab age_categories if survey==1

age_categor |
        ies |      Freq.     Percent        Cum.
------------+-----------------------------------
      35-49 |         29       25.89       25.89
      50-64 |         60       53.57       79.46
       < 35 |          8        7.14       86.61
       > 64 |         15       13.39      100.00
------------+-----------------------------------
      Total |        112      100.00

. *Seniority
. tab seniority_categories if survey==1

  Seniority |
 Categories |      Freq.     Percent        Cum.
------------+-----------------------------------
        4-7 |         29       25.89       25.89
       8-11 |         15       13.39       39.29
        < 4 |         45       40.18       79.46
        >11 |         23       20.54      100.00
------------+-----------------------------------
      Total |        112      100.00

. *Committee
. tab committee_2010_2014 if survey==1

committee_2 |
   010_2014 |      Freq.     Percent        Cum.
------------+-----------------------------------
legislative |         68       60.71       60.71
  oversight |         44       39.29      100.00
------------+-----------------------------------
      Total |        112      100.00

. *Interventions
. tab interventions_categories if survey==1

Interventio |
         ns |
 Categories |      Freq.     Percent        Cum.
------------+-----------------------------------
      10-19 |         31       27.68       27.68
      20-29 |         20       17.86       45.54
        <10 |         23       20.54       66.07
        >30 |         38       33.93      100.00
------------+-----------------------------------
      Total |        112      100.00

. 
. *Survey Participation Probit-Model (Model 1)
. probit survey ib1.sex c.age ib1.lang_d ib1.party_grp c.int_count_d

Iteration 0:   log likelihood = -168.91995  
Iteration 1:   log likelihood = -164.98495  
Iteration 2:   log likelihood = -164.98133  
Iteration 3:   log likelihood = -164.98133  

Probit regression                                 Number of obs   =        245
                                                  LR chi2(6)      =       7.88
                                                  Prob > chi2     =     0.2472
Log likelihood = -164.98133                       Pseudo R2       =     0.0233

------------------------------------------------------------------------------
      survey |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sex |
       male  |  -.2552112   .1883676    -1.35   0.175    -.6244049    .1139825
         age |   .0037686   .0082686     0.46   0.649    -.0124376    .0199747
             |
      lang_d |
      latin  |   .1723469   .1837403     0.94   0.348    -.1877775    .5324713
             |
   party_grp |
     center  |   .2743007    .205916     1.33   0.183    -.1292872    .6778887
       left  |   .4228506   .2398385     1.76   0.078    -.0472242    .8929254
             |
 int_count_d |  -.1422756   .1196496    -1.19   0.234    -.3767845    .0922334
       _cons |  -.3590222   .5000332    -0.72   0.473    -1.339069    .6210249
------------------------------------------------------------------------------

. 
. *Overreport Probit Model (Model 2)
. probit over_report ib1.sex c.age ib1.lang_d ib1.party_grp c.prof c.att c.int_
> count_d 

Iteration 0:   log likelihood = -69.169746  
Iteration 1:   log likelihood = -59.807742  
Iteration 2:   log likelihood = -59.715883  
Iteration 3:   log likelihood = -59.715771  
Iteration 4:   log likelihood = -59.715771  

Probit regression                                 Number of obs   =        106
                                                  LR chi2(8)      =      18.91
                                                  Prob > chi2     =     0.0154
Log likelihood = -59.715771                       Pseudo R2       =     0.1367

------------------------------------------------------------------------------
 over_report |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sex |
       male  |  -.3960164   .3027278    -1.31   0.191     -.989352    .1973191
         age |  -.0063326   .0126563    -0.50   0.617    -.0311386    .0184734
             |
      lang_d |
      latin  |   .4571095   .2951884     1.55   0.121    -.1214492    1.035668
             |
   party_grp |
     center  |   .3033451     .37808     0.80   0.422    -.4376781    1.044368
       left  |  -.1057759    .430115    -0.25   0.806    -.9487859    .7372341
             |
        prof |  -.2125438   .9186469    -0.23   0.817    -2.013059    1.587971
         att |   .4365776   .2514277     1.74   0.082    -.0562117    .9293668
 int_count_d |  -.6423369   .2303701    -2.79   0.005    -1.093854   -.1908198
       _cons |  -.9961611   1.186248    -0.84   0.401    -3.321165    1.328842
------------------------------------------------------------------------------

. 
. *Predicted Probabilities Survey Overreporting (Figure 2)
. margins, at(att=(1(0.02)4) sex=(0 1) lang_d=1 party_grp=2 (mean) _all )

Adjusted predictions                              Number of obs   =        106
Model VCE    : OIM

Expression   : Pr(over_report), predict()

1._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =           1
               int_count_d     =    .4811321 (mean)

2._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.02
               int_count_d     =    .4811321 (mean)

3._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.04
               int_count_d     =    .4811321 (mean)

4._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.06
               int_count_d     =    .4811321 (mean)

5._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.08
               int_count_d     =    .4811321 (mean)

6._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.1
               int_count_d     =    .4811321 (mean)

7._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.12
               int_count_d     =    .4811321 (mean)

8._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.14
               int_count_d     =    .4811321 (mean)

9._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.16
               int_count_d     =    .4811321 (mean)

10._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.18
               int_count_d     =    .4811321 (mean)

11._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.2
               int_count_d     =    .4811321 (mean)

12._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.22
               int_count_d     =    .4811321 (mean)

13._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.24
               int_count_d     =    .4811321 (mean)

14._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.26
               int_count_d     =    .4811321 (mean)

15._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.28
               int_count_d     =    .4811321 (mean)

16._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.3
               int_count_d     =    .4811321 (mean)

17._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.32
               int_count_d     =    .4811321 (mean)

18._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.34
               int_count_d     =    .4811321 (mean)

19._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.36
               int_count_d     =    .4811321 (mean)

20._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.38
               int_count_d     =    .4811321 (mean)

21._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.4
               int_count_d     =    .4811321 (mean)

22._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.42
               int_count_d     =    .4811321 (mean)

23._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.44
               int_count_d     =    .4811321 (mean)

24._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.46
               int_count_d     =    .4811321 (mean)

25._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.48
               int_count_d     =    .4811321 (mean)

26._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.5
               int_count_d     =    .4811321 (mean)

27._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.52
               int_count_d     =    .4811321 (mean)

28._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.54
               int_count_d     =    .4811321 (mean)

29._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.56
               int_count_d     =    .4811321 (mean)

30._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.58
               int_count_d     =    .4811321 (mean)

31._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.6
               int_count_d     =    .4811321 (mean)

32._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.62
               int_count_d     =    .4811321 (mean)

33._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.64
               int_count_d     =    .4811321 (mean)

34._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.66
               int_count_d     =    .4811321 (mean)

35._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.68
               int_count_d     =    .4811321 (mean)

36._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.7
               int_count_d     =    .4811321 (mean)

37._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.72
               int_count_d     =    .4811321 (mean)

38._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.74
               int_count_d     =    .4811321 (mean)

39._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.76
               int_count_d     =    .4811321 (mean)

40._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.78
               int_count_d     =    .4811321 (mean)

41._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.8
               int_count_d     =    .4811321 (mean)

42._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.82
               int_count_d     =    .4811321 (mean)

43._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.84
               int_count_d     =    .4811321 (mean)

44._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.86
               int_count_d     =    .4811321 (mean)

45._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.88
               int_count_d     =    .4811321 (mean)

46._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.9
               int_count_d     =    .4811321 (mean)

47._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.92
               int_count_d     =    .4811321 (mean)

48._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.94
               int_count_d     =    .4811321 (mean)

49._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.96
               int_count_d     =    .4811321 (mean)

50._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
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               att             =        2.62
               int_count_d     =    .4811321 (mean)

234._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.64
               int_count_d     =    .4811321 (mean)

235._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.66
               int_count_d     =    .4811321 (mean)

236._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.68
               int_count_d     =    .4811321 (mean)

237._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         2.7
               int_count_d     =    .4811321 (mean)

238._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.72
               int_count_d     =    .4811321 (mean)

239._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.74
               int_count_d     =    .4811321 (mean)

240._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.76
               int_count_d     =    .4811321 (mean)

241._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.78
               int_count_d     =    .4811321 (mean)

242._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         2.8
               int_count_d     =    .4811321 (mean)

243._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.82
               int_count_d     =    .4811321 (mean)

244._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.84
               int_count_d     =    .4811321 (mean)

245._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.86
               int_count_d     =    .4811321 (mean)

246._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.88
               int_count_d     =    .4811321 (mean)

247._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         2.9
               int_count_d     =    .4811321 (mean)

248._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.92
               int_count_d     =    .4811321 (mean)

249._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.94
               int_count_d     =    .4811321 (mean)

250._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.96
               int_count_d     =    .4811321 (mean)

251._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.98
               int_count_d     =    .4811321 (mean)

252._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =           3
               int_count_d     =    .4811321 (mean)

253._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.02
               int_count_d     =    .4811321 (mean)

254._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.04
               int_count_d     =    .4811321 (mean)

255._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.06
               int_count_d     =    .4811321 (mean)

256._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.08
               int_count_d     =    .4811321 (mean)

257._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.1
               int_count_d     =    .4811321 (mean)

258._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.12
               int_count_d     =    .4811321 (mean)

259._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.14
               int_count_d     =    .4811321 (mean)

260._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.16
               int_count_d     =    .4811321 (mean)

261._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.18
               int_count_d     =    .4811321 (mean)

262._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.2
               int_count_d     =    .4811321 (mean)

263._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.22
               int_count_d     =    .4811321 (mean)

264._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.24
               int_count_d     =    .4811321 (mean)

265._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.26
               int_count_d     =    .4811321 (mean)

266._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.28
               int_count_d     =    .4811321 (mean)

267._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.3
               int_count_d     =    .4811321 (mean)

268._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.32
               int_count_d     =    .4811321 (mean)

269._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.34
               int_count_d     =    .4811321 (mean)

270._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.36
               int_count_d     =    .4811321 (mean)

271._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.38
               int_count_d     =    .4811321 (mean)

272._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.4
               int_count_d     =    .4811321 (mean)

273._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.42
               int_count_d     =    .4811321 (mean)

274._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.44
               int_count_d     =    .4811321 (mean)

275._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.46
               int_count_d     =    .4811321 (mean)

276._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.48
               int_count_d     =    .4811321 (mean)

277._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.5
               int_count_d     =    .4811321 (mean)

278._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.52
               int_count_d     =    .4811321 (mean)

279._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.54
               int_count_d     =    .4811321 (mean)

280._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.56
               int_count_d     =    .4811321 (mean)

281._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.58
               int_count_d     =    .4811321 (mean)

282._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.6
               int_count_d     =    .4811321 (mean)

283._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.62
               int_count_d     =    .4811321 (mean)

284._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.64
               int_count_d     =    .4811321 (mean)

285._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.66
               int_count_d     =    .4811321 (mean)

286._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.68
               int_count_d     =    .4811321 (mean)

287._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.7
               int_count_d     =    .4811321 (mean)

288._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.72
               int_count_d     =    .4811321 (mean)

289._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.74
               int_count_d     =    .4811321 (mean)

290._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.76
               int_count_d     =    .4811321 (mean)

291._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.78
               int_count_d     =    .4811321 (mean)

292._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.8
               int_count_d     =    .4811321 (mean)

293._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.82
               int_count_d     =    .4811321 (mean)

294._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.84
               int_count_d     =    .4811321 (mean)

295._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.86
               int_count_d     =    .4811321 (mean)

296._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.88
               int_count_d     =    .4811321 (mean)

297._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.9
               int_count_d     =    .4811321 (mean)

298._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.92
               int_count_d     =    .4811321 (mean)

299._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.94
               int_count_d     =    .4811321 (mean)

300._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.96
               int_count_d     =    .4811321 (mean)

301._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.98
               int_count_d     =    .4811321 (mean)

302._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =           4
               int_count_d     =    .4811321 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .0752482   .0802124     0.94   0.348    -.0819651    .2324615
          2  |   .0764951    .080577     0.95   0.342    -.0814328     .234423
          3  |   .0777577   .0809332     0.96   0.337    -.0808684    .2363838
          4  |    .079036   .0812809     0.97   0.331    -.0802716    .2383436
          5  |   .0803302   .0816199     0.98   0.325    -.0796419    .2403023
          6  |   .0816403   .0819502     1.00   0.319     -.078979    .2422597
          7  |   .0829665   .0822715     1.01   0.313    -.0782826    .2442156
          8  |   .0843088   .0825837     1.02   0.307    -.0775523    .2461699
          9  |   .0856673   .0828868     1.03   0.301    -.0767877    .2481224
         10  |   .0870422   .0831805     1.05   0.295    -.0759886     .250073
         11  |   .0884335   .0834648     1.06   0.289    -.0751545    .2520215
         12  |   .0898413   .0837396     1.07   0.283    -.0742853    .2539678
         13  |   .0912656   .0840047     1.09   0.277    -.0733806    .2559118
         14  |   .0927067   .0842601     1.10   0.271      -.07244    .2578534
         15  |   .0941645   .0845056     1.11   0.265    -.0714635    .2597924
         16  |   .0956391   .0847412     1.13   0.259    -.0704506    .2617288
         17  |   .0971307   .0849668     1.14   0.253    -.0694011    .2636625
         18  |   .0986393   .0851823     1.16   0.247    -.0683149    .2655934
         19  |   .1001649   .0853876     1.17   0.241    -.0671916    .2675215
         20  |   .1017077   .0855826     1.19   0.235    -.0660311    .2694466
         21  |   .1032678   .0857674     1.20   0.229    -.0648333    .2713688
         22  |   .1048451   .0859419     1.22   0.222    -.0635978     .273288
         23  |   .1064398   .0861059     1.24   0.216    -.0623246    .2752043
         24  |    .108052   .0862596     1.25   0.210    -.0610136    .2771176
         25  |   .1096816   .0864027     1.27   0.204    -.0596646    .2790279
         26  |   .1113289   .0865355     1.29   0.198    -.0582776    .2809353
         27  |   .1129937   .0866578     1.30   0.192    -.0568524    .2828398
         28  |   .1146763   .0867696     1.32   0.186     -.055389    .2847415
         29  |   .1163766   .0868709     1.34   0.180    -.0538873    .2866405
         30  |   .1180947   .0869619     1.36   0.174    -.0523474    .2885368
         31  |   .1198307   .0870424     1.38   0.169    -.0507693    .2904307
         32  |   .1215846   .0871126     1.40   0.163     -.049153    .2923221
         33  |   .1233564   .0871725     1.42   0.157    -.0474985    .2942113
         34  |   .1251463   .0872221     1.43   0.151    -.0458059    .2960985
         35  |   .1269542   .0872616     1.45   0.146    -.0440754    .2979838
         36  |   .1287802    .087291     1.48   0.140     -.042307    .2998675
         37  |   .1306244   .0873105     1.50   0.135     -.040501    .3017498
         38  |   .1324868   .0873201     1.52   0.129    -.0386575     .303631
         39  |   .1343673     .08732     1.54   0.124    -.0367768    .3055114
         40  |   .1362661   .0873104     1.56   0.119     -.034859    .3073913
         41  |   .1381832   .0872913     1.58   0.113    -.0329046     .309271
         42  |   .1401186    .087263     1.61   0.108    -.0309137    .3111509
         43  |   .1420723   .0872256     1.63   0.103    -.0288868    .3130315
         44  |   .1440444   .0871795     1.65   0.098    -.0268242     .314913
         45  |   .1460349   .0871246     1.68   0.094    -.0247263    .3167961
         46  |   .1480437   .0870615     1.70   0.089    -.0225936    .3186811
         47  |    .150071   .0869902     1.73   0.085    -.0204266    .3205686
         48  |   .1521167    .086911     1.75   0.080    -.0182257    .3224591
         49  |   .1541808   .0868243     1.78   0.076    -.0159916    .3243533
         50  |   .1562634   .0867303     1.80   0.072    -.0137249    .3262518
         51  |   .1583644   .0866295     1.83   0.068    -.0114262    .3281551
         52  |   .1604839    .086522     1.85   0.064    -.0090962     .330064
         53  |   .1626218   .0864084     1.88   0.060    -.0067356    .3319792
         54  |   .1647781    .086289     1.91   0.056    -.0043452    .3339014
         55  |   .1669529   .0861642     1.94   0.053    -.0019257    .3358316
         56  |   .1691461   .0860344     1.97   0.049     .0005219    .3377704
         57  |   .1713578   .0859001     1.99   0.046     .0029967    .3397188
         58  |   .1735878   .0857618     2.02   0.043     .0054979    .3416778
         59  |   .1758362   .0856199     2.05   0.040     .0080243    .3436481
         60  |    .178103    .085475     2.08   0.037      .010575     .345631
         61  |   .1803881   .0853277     2.11   0.035     .0131489    .3476273
         62  |   .1826915   .0851784     2.14   0.032     .0157448    .3496382
         63  |   .1850132   .0850279     2.18   0.030     .0183616    .3516648
         64  |   .1873531   .0848766     2.21   0.027      .020998    .3537082
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         66  |   .1920875   .0845745     2.27   0.023     .0263245    .3578506
         67  |   .1944819   .0844251     2.30   0.021     .0290119     .359952
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         69  |    .199325   .0841327     2.37   0.018     .0344278    .3642221
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         71  |     .20424   .0838542     2.44   0.015     .0398887    .3685912
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         74  |   .2117462    .083476     2.54   0.011     .0481362    .3753562
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         79  |    .224609   .0830072     2.71   0.007      .061918    .3873001
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         81  |   .2298757   .0828968     2.77   0.006      .067401    .3923505
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         83  |   .2352109   .0828415     2.84   0.005     .0728445    .3975773
         84  |   .2379039   .0828369     2.87   0.004     .0755465    .4002612
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         87  |   .2460833   .0829261     2.97   0.003     .0835513    .4086154
         88  |    .248843   .0829932     3.00   0.003     .0861793    .4115067
         89  |    .251619   .0830806     3.03   0.002      .088784     .414454
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         91  |   .2572197   .0833195     3.09   0.002     .0939165     .420523
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         93  |   .2628846   .0836497     3.14   0.002     .0989343    .4268349
         94  |   .2657408   .0838509     3.17   0.002     .1013959    .4300856
         95  |   .2686126   .0840774     3.19   0.001     .1038239    .4334013
         96  |      .2715   .0843298     3.22   0.001     .1062167    .4367833
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         98  |   .2773206   .0849149     3.27   0.001     .1108905    .4437507
         99  |   .2802536   .0852489     3.29   0.001      .113169    .4473383
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        108  |   .3073049   .0895834     3.43   0.001     .1317247    .4828852
        109  |   .3103803   .0902183     3.44   0.001     .1335556     .487205
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        111  |   .3165709   .0915819     3.46   0.001     .1370737     .496068
        112  |   .3196857   .0923104     3.46   0.001     .1387606    .5006107
        113  |   .3228132     .09307     3.47   0.001     .1403994     .505227
        114  |   .3259534   .0938604     3.47   0.001     .1419903    .5099164
        115  |   .3291059   .0946816     3.48   0.001     .1435334    .5146784
        116  |   .3322706   .0955332     3.48   0.001      .145029    .5195123
        117  |   .3354474   .0964149     3.48   0.001     .1464776    .5244172
        118  |   .3386359   .0973265     3.48   0.001     .1478795    .5293923
        119  |   .3418361   .0982675     3.48   0.001     .1492354    .5344368
        120  |   .3450477   .0992375     3.48   0.001     .1505459    .5395495
        121  |   .3482705    .100236     3.47   0.001     .1518115    .5447294
        122  |   .3515042   .1012626     3.47   0.001     .1530331    .5499753
        123  |   .3547488   .1023168     3.47   0.001     .1542115    .5552861
        124  |   .3580039    .103398     3.46   0.001     .1553475    .5606603
        125  |   .3612694   .1045057     3.46   0.001      .156442    .5660967
        126  |    .364545   .1056392     3.45   0.001      .157496     .571594
        127  |   .3678305   .1067979     3.44   0.001     .1585105    .5771506
        128  |   .3711258   .1079812     3.44   0.001     .1594864    .5827651
        129  |   .3744305   .1091885     3.43   0.001      .160425     .588436
        130  |   .3777444    .110419     3.42   0.001     .1613272    .5941617
        131  |   .3810674   .1116721     3.41   0.001     .1621942    .5999407
        132  |   .3843992    .112947     3.40   0.001     .1630271    .6057713
        133  |   .3877396   .1142431     3.39   0.001     .1638272     .611652
        134  |   .3910882   .1155596     3.38   0.001     .1645955    .6175809
        135  |    .394445   .1168958     3.37   0.001     .1653334    .6235566
        136  |   .3978096    .118251     3.36   0.001      .166042    .6295772
        137  |   .4011818   .1196243     3.35   0.001     .1667225    .6356412
        138  |   .4045615   .1210151     3.34   0.001     .1673762    .6417467
        139  |   .4079482   .1224226     3.33   0.001     .1680044    .6478921
        140  |   .4113419    .123846     3.32   0.001     .1686082    .6540755
        141  |   .4147421   .1252846     3.31   0.001     .1691888    .6602954
        142  |   .4181488   .1267376     3.30   0.001     .1697477      .66655
        143  |   .4215617   .1282043     3.29   0.001     .1702859    .6728374
        144  |   .4249804   .1296839     3.28   0.001     .1708047    .6791561
        145  |   .4284048   .1311756     3.27   0.001     .1713054    .6855043
        146  |   .4318346   .1326787     3.25   0.001     .1717892    .6918801
        147  |   .4352696   .1341924     3.24   0.001     .1722573    .6982819
        148  |   .4387094    .135716     3.23   0.001     .1727109    .7047079
        149  |   .4421539   .1372488     3.22   0.001     .1731512    .7111566
        150  |   .4456027   .1387899     3.21   0.001     .1735794     .717626
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        176  |   .2026462   .1407207     1.44   0.150    -.0731613    .4784537
        177  |    .205119   .1405431     1.46   0.144    -.0703405    .4805785
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        182  |   .2177492   .1394136     1.56   0.118    -.0554964    .4909948
        183  |   .2203281   .1391403     1.58   0.113    -.0523819     .493038
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        185  |   .2255379   .1385477     1.63   0.104    -.0460106    .4970865
        186  |   .2281688   .1382288     1.65   0.099    -.0427548    .4990923
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        188  |   .2334819    .137547     1.70   0.090    -.0361052    .5030691
        189  |    .236164   .1371845     1.72   0.085    -.0327127    .5050407
        190  |    .238863    .136808     1.75   0.081    -.0292757    .5070017
        191  |   .2415787   .1364177     1.77   0.077     -.025795    .5089525
        192  |   .2443111   .1360139     1.80   0.072    -.0222713    .5108936
        193  |   .2470602    .135597     1.82   0.068    -.0187051    .5128255
        194  |   .2498256   .1351673     1.85   0.065    -.0150974    .5147486
        195  |   .2526074    .134725     1.87   0.061    -.0114488    .5166636
        196  |   .2554055   .1342706     1.90   0.057    -.0077601     .518571
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        198  |   .2610498   .1333268     1.96   0.050     -.000266    .5223655
        199  |   .2638958   .1328382     1.99   0.047     .0035377    .5242538
        200  |   .2667575    .132339     2.02   0.044     .0073779    .5261371
        201  |   .2696348   .1318296     2.05   0.041     .0112536    .5280161
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        203  |   .2754358   .1307821     2.11   0.035     .0191075    .5317641
        204  |   .2783591    .130245     2.14   0.033     .0230835    .5336346
        205  |   .2812974   .1296996     2.17   0.030     .0270909     .535504
        206  |   .2842507   .1291465     2.20   0.028     .0311283    .5373731
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        209  |   .2931983   .1274458     2.30   0.021     .0434091    .5429874
        210  |   .2962095   .1268671     2.33   0.020     .0475546    .5448644
        211  |   .2992349   .1262834     2.37   0.018      .051724    .5467459
        212  |   .3022743   .1256955     2.40   0.016     .0559157    .5486328
        213  |   .3053274   .1251038     2.44   0.015     .0601283    .5505264
        214  |   .3083941   .1245092     2.48   0.013     .0643605    .5524276
        215  |   .3114742   .1239122     2.51   0.012     .0686108    .5543376
        216  |   .3145676   .1233135     2.55   0.011     .0728775    .5562576
        217  |    .317674   .1227139     2.59   0.010     .0771592    .5581888
        218  |   .3207934    .122114     2.63   0.009     .0814543    .5601325
        219  |   .3239254   .1215147     2.67   0.008     .0857611    .5620898
        220  |     .32707   .1209165     2.70   0.007     .0900779     .564062
        221  |   .3302269   .1203204     2.74   0.006     .0944032    .5660506
        222  |   .3333959   .1197271     2.78   0.005     .0987351    .5680568
        223  |   .3365769   .1191374     2.83   0.005     .1030718    .5700819
        224  |   .3397696   .1185521     2.87   0.004     .1074117    .5721275
        225  |   .3429738    .117972     2.91   0.004     .1117529    .5741948
        226  |   .3461894    .117398     2.95   0.003     .1160935    .5762853
        227  |   .3494161   .1168309     2.99   0.003     .1204317    .5784004
        228  |   .3526537   .1162715     3.03   0.002     .1247657    .5805417
        229  |    .355902   .1157208     3.08   0.002     .1290935    .5827106
        230  |   .3591608   .1151795     3.12   0.002     .1334131    .5849085
        231  |   .3624299   .1146486     3.16   0.002     .1377228     .587137
        232  |   .3657091   .1141289     3.20   0.001     .1420205    .5893977
        233  |   .3689981   .1136214     3.25   0.001     .1463042    .5916919
        234  |   .3722967   .1131268     3.29   0.001     .1505722    .5940213
        235  |   .3756047   .1126462     3.33   0.001     .1548223    .5963872
        236  |   .3789219   .1121803     3.38   0.001     .1590526    .5987913
        237  |   .3822481     .11173     3.42   0.001     .1632612    .6012349
        238  |   .3855829   .1112963     3.46   0.001     .1674462    .6037196
        239  |   .3889262   .1108799     3.51   0.000     .1716056    .6062468
        240  |   .3922778   .1104817     3.55   0.000     .1757376    .6088179
        241  |   .3956373   .1101026     3.59   0.000     .1798403    .6114344
        242  |   .3990047   .1097433     3.64   0.000     .1839119    .6140975
        243  |   .4023796   .1094046     3.68   0.000     .1879505    .6168087
        244  |   .4057617   .1090874     3.72   0.000     .1919544    .6195691
        245  |    .409151   .1087924     3.76   0.000     .1959219    .6223801
        246  |    .412547   .1085202     3.80   0.000     .1998513    .6252428
        247  |   .4159496   .1082717     3.84   0.000      .203741    .6281582
        248  |   .4193585   .1080474     3.88   0.000     .2075895    .6311275
        249  |   .4227735    .107848     3.92   0.000     .2113953    .6341517
        250  |   .4261943   .1076741     3.96   0.000     .2151569    .6372316
        251  |   .4296206   .1075262     4.00   0.000     .2188731    .6403681
        252  |   .4330522   .1074049     4.03   0.000     .2225425     .643562
        253  |   .4364889   .1073106     4.07   0.000      .226164    .6468139
        254  |   .4399304   .1072437     4.10   0.000     .2297366    .6501243
        255  |   .4433765   .1072047     4.14   0.000     .2332591    .6534939
        256  |   .4468268   .1071938     4.17   0.000     .2367308    .6569228
        257  |   .4502812   .1072113     4.20   0.000     .2401508    .6604116
        258  |   .4537393   .1072575     4.23   0.000     .2435185    .6639602
        259  |    .457201   .1073325     4.26   0.000     .2468331    .6675689
        260  |   .4606659   .1074365     4.29   0.000     .2500943    .6712376
        261  |   .4641338   .1075695     4.31   0.000     .2533015    .6749661
        262  |   .4676044   .1077315     4.34   0.000     .2564546    .6787542
        263  |   .4710775   .1079225     4.36   0.000     .2595533    .6826017
        264  |   .4745528   .1081424     4.39   0.000     .2625976     .686508
        265  |     .47803   .1083911     4.41   0.000     .2655874    .6904726
        266  |   .4815089   .1086683     4.43   0.000      .268523    .6944948
        267  |   .4849892   .1089739     4.45   0.000     .2714044     .698574
        268  |   .4884706   .1093074     4.47   0.000      .274232    .7027093
        269  |    .491953   .1096687     4.49   0.000     .2770063    .7068997
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        297  |   .5887424   .1285301     4.58   0.000     .3368281    .8406568
        298  |   .5921359   .1294037     4.58   0.000     .3385092    .8457626
        299  |   .5955225   .1302828     4.57   0.000     .3401728    .8508722
        300  |   .5989019   .1311666     4.57   0.000     .3418201    .8559837
        301  |    .602274   .1320541     4.56   0.000     .3434526    .8610953
        302  |   .6056384   .1329447     4.56   0.000     .3450715    .8662053
------------------------------------------------------------------------------

. marginsplot, ///
> scheme(s1mono) graphregion(fcolor(white) ilcolor(white) lcolor(white))

  Variables that uniquely identify margins: att sex

. 
. *Undereport Probit (Model 3)
. probit under_report ib1.sex c.age ib1.lang_d ib1.party_grp c.prof c.att c.int
> _count_d

Iteration 0:   log likelihood = -37.435955  
Iteration 1:   log likelihood = -20.300517  
Iteration 2:   log likelihood = -16.446601  
Iteration 3:   log likelihood = -16.129772  
Iteration 4:   log likelihood =  -16.12692  
Iteration 5:   log likelihood = -16.126918  
Iteration 6:   log likelihood = -16.126918  

Probit regression                                 Number of obs   =        106
                                                  LR chi2(8)      =      42.62
                                                  Prob > chi2     =     0.0000
Log likelihood = -16.126918                       Pseudo R2       =     0.5692

------------------------------------------------------------------------------
under_report |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         sex |
       male  |   2.604277   .9079535     2.87   0.004     .8247207    4.383833
         age |  -.0379868   .0259446    -1.46   0.143    -.0888372    .0128636
             |
      lang_d |
      latin  |  -.5989266   .7076375    -0.85   0.397    -1.985871    .7880173
             |
   party_grp |
     center  |    .379297   .9819049     0.39   0.699    -1.545201    2.303795
       left  |   .0390719   .9794655     0.04   0.968    -1.880645    1.958789
             |
        prof |    1.98638   1.918533     1.04   0.300    -1.773876    5.746636
         att |    -.92012   .4247696    -2.17   0.030    -1.752653   -.0875868
 int_count_d |   2.227005   .5747787     3.87   0.000     1.100459     3.35355
       _cons |  -1.803594   2.532637    -0.71   0.476    -6.767472    3.160283
------------------------------------------------------------------------------
Note: 5 failures and 0 successes completely determined.

. 
. *Predicted Probabilities Survey Underreporting (Figure 3)
. margins, at(att=(1(0.02)4) lang_d=1 sex=(0 1) party_grp=2 (mean) _all )

Adjusted predictions                              Number of obs   =        106
Model VCE    : OIM

Expression   : Pr(under_report), predict()

1._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =           1
               int_count_d     =    .4811321 (mean)

2._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.02
               int_count_d     =    .4811321 (mean)

3._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.04
               int_count_d     =    .4811321 (mean)

4._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.06
               int_count_d     =    .4811321 (mean)

5._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.08
               int_count_d     =    .4811321 (mean)

6._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.1
               int_count_d     =    .4811321 (mean)

7._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.12
               int_count_d     =    .4811321 (mean)

8._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.14
               int_count_d     =    .4811321 (mean)

9._at        : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.16
               int_count_d     =    .4811321 (mean)

10._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.18
               int_count_d     =    .4811321 (mean)

11._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.2
               int_count_d     =    .4811321 (mean)

12._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.22
               int_count_d     =    .4811321 (mean)

13._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.24
               int_count_d     =    .4811321 (mean)

14._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.26
               int_count_d     =    .4811321 (mean)

15._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.28
               int_count_d     =    .4811321 (mean)

16._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.3
               int_count_d     =    .4811321 (mean)

17._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.32
               int_count_d     =    .4811321 (mean)

18._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.34
               int_count_d     =    .4811321 (mean)

19._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.36
               int_count_d     =    .4811321 (mean)

20._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.38
               int_count_d     =    .4811321 (mean)

21._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.4
               int_count_d     =    .4811321 (mean)

22._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.42
               int_count_d     =    .4811321 (mean)

23._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.44
               int_count_d     =    .4811321 (mean)

24._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.46
               int_count_d     =    .4811321 (mean)

25._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.48
               int_count_d     =    .4811321 (mean)

26._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.5
               int_count_d     =    .4811321 (mean)

27._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.52
               int_count_d     =    .4811321 (mean)

28._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.54
               int_count_d     =    .4811321 (mean)

29._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.56
               int_count_d     =    .4811321 (mean)

30._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.58
               int_count_d     =    .4811321 (mean)

31._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.6
               int_count_d     =    .4811321 (mean)

32._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.62
               int_count_d     =    .4811321 (mean)

33._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.64
               int_count_d     =    .4811321 (mean)

34._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.66
               int_count_d     =    .4811321 (mean)

35._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.68
               int_count_d     =    .4811321 (mean)

36._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.7
               int_count_d     =    .4811321 (mean)

37._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.72
               int_count_d     =    .4811321 (mean)

38._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.74
               int_count_d     =    .4811321 (mean)

39._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.76
               int_count_d     =    .4811321 (mean)

40._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.78
               int_count_d     =    .4811321 (mean)

41._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.8
               int_count_d     =    .4811321 (mean)

42._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.82
               int_count_d     =    .4811321 (mean)

43._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.84
               int_count_d     =    .4811321 (mean)

44._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.86
               int_count_d     =    .4811321 (mean)

45._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.88
               int_count_d     =    .4811321 (mean)

46._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         1.9
               int_count_d     =    .4811321 (mean)

47._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.92
               int_count_d     =    .4811321 (mean)

48._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.94
               int_count_d     =    .4811321 (mean)

49._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.96
               int_count_d     =    .4811321 (mean)

50._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        1.98
               int_count_d     =    .4811321 (mean)

51._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =           2
               int_count_d     =    .4811321 (mean)

52._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.02
               int_count_d     =    .4811321 (mean)

53._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.04
               int_count_d     =    .4811321 (mean)

54._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.06
               int_count_d     =    .4811321 (mean)

55._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.08
               int_count_d     =    .4811321 (mean)

56._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         2.1
               int_count_d     =    .4811321 (mean)

57._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.12
               int_count_d     =    .4811321 (mean)

58._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.14
               int_count_d     =    .4811321 (mean)

59._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.16
               int_count_d     =    .4811321 (mean)

60._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.18
               int_count_d     =    .4811321 (mean)

61._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         2.2
               int_count_d     =    .4811321 (mean)

62._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.22
               int_count_d     =    .4811321 (mean)

63._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.24
               int_count_d     =    .4811321 (mean)

64._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.26
               int_count_d     =    .4811321 (mean)

65._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.28
               int_count_d     =    .4811321 (mean)

66._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         2.3
               int_count_d     =    .4811321 (mean)

67._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.32
               int_count_d     =    .4811321 (mean)

68._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.34
               int_count_d     =    .4811321 (mean)

69._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.36
               int_count_d     =    .4811321 (mean)

70._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.38
               int_count_d     =    .4811321 (mean)

71._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         2.4
               int_count_d     =    .4811321 (mean)

72._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.42
               int_count_d     =    .4811321 (mean)

73._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.44
               int_count_d     =    .4811321 (mean)

74._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.46
               int_count_d     =    .4811321 (mean)

75._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.48
               int_count_d     =    .4811321 (mean)

76._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         2.5
               int_count_d     =    .4811321 (mean)

77._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.52
               int_count_d     =    .4811321 (mean)

78._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.54
               int_count_d     =    .4811321 (mean)

79._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.56
               int_count_d     =    .4811321 (mean)

80._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        2.58
               int_count_d     =    .4811321 (mean)

81._at       : sex             =           0
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
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197._at      : sex             =           1
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203._at      : sex             =           1
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204._at      : sex             =           1
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205._at      : sex             =           1
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               int_count_d     =    .4811321 (mean)

265._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.26
               int_count_d     =    .4811321 (mean)

266._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.28
               int_count_d     =    .4811321 (mean)

267._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.3
               int_count_d     =    .4811321 (mean)

268._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.32
               int_count_d     =    .4811321 (mean)

269._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.34
               int_count_d     =    .4811321 (mean)

270._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.36
               int_count_d     =    .4811321 (mean)

271._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.38
               int_count_d     =    .4811321 (mean)

272._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.4
               int_count_d     =    .4811321 (mean)

273._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.42
               int_count_d     =    .4811321 (mean)

274._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.44
               int_count_d     =    .4811321 (mean)

275._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.46
               int_count_d     =    .4811321 (mean)

276._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.48
               int_count_d     =    .4811321 (mean)

277._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.5
               int_count_d     =    .4811321 (mean)

278._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.52
               int_count_d     =    .4811321 (mean)

279._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.54
               int_count_d     =    .4811321 (mean)

280._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.56
               int_count_d     =    .4811321 (mean)

281._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.58
               int_count_d     =    .4811321 (mean)

282._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.6
               int_count_d     =    .4811321 (mean)

283._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.62
               int_count_d     =    .4811321 (mean)

284._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.64
               int_count_d     =    .4811321 (mean)

285._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.66
               int_count_d     =    .4811321 (mean)

286._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.68
               int_count_d     =    .4811321 (mean)

287._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.7
               int_count_d     =    .4811321 (mean)

288._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.72
               int_count_d     =    .4811321 (mean)

289._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.74
               int_count_d     =    .4811321 (mean)

290._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.76
               int_count_d     =    .4811321 (mean)

291._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.78
               int_count_d     =    .4811321 (mean)

292._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.8
               int_count_d     =    .4811321 (mean)

293._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.82
               int_count_d     =    .4811321 (mean)

294._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.84
               int_count_d     =    .4811321 (mean)

295._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.86
               int_count_d     =    .4811321 (mean)

296._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.88
               int_count_d     =    .4811321 (mean)

297._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =         3.9
               int_count_d     =    .4811321 (mean)

298._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.92
               int_count_d     =    .4811321 (mean)

299._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.94
               int_count_d     =    .4811321 (mean)

300._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.96
               int_count_d     =    .4811321 (mean)

301._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =        3.98
               int_count_d     =    .4811321 (mean)

302._at      : sex             =           1
               age             =    53.73585 (mean)
               lang_d          =           1
               party_grp       =           2
               prof            =    .6407547 (mean)
               att             =           4
               int_count_d     =    .4811321 (mean)

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         _at |
          1  |   .7132395   .3050602     2.34   0.019     .1153325    1.311147
          2  |   .7069414    .305833     2.31   0.021     .1075196    1.306363
          3  |   .7005798   .3064959     2.29   0.022     .0998589    1.301301
          4  |   .6941564   .3070483     2.26   0.024     .0923527     1.29596
          5  |   .6876726   .3074898     2.24   0.025     .0850036    1.290342
          6  |   .6811302   .3078202     2.21   0.027     .0778137    1.284447
          7  |   .6745309   .3080393     2.19   0.029     .0707851    1.278277
          8  |   .6678764   .3081471     2.17   0.030     .0639193    1.271834
          9  |   .6611686   .3081437     2.15   0.032      .057218    1.265119
         10  |   .6544092   .3080295     2.12   0.034     .0506824    1.258136
         11  |   .6476002   .3078049     2.10   0.035     .0443137    1.250887
         12  |   .6407436   .3074704     2.08   0.037     .0381126    1.243375
         13  |   .6338414   .3070268     2.06   0.039       .03208    1.235603
         14  |   .6268956   .3064748     2.05   0.041     .0262161    1.227575
         15  |   .6199083   .3058153     2.03   0.043     .0205213    1.219295
         16  |   .6128817   .3050496     2.01   0.045     .0149954    1.210768
         17  |   .6058178   .3041788     1.99   0.046     .0096383    1.201997
         18  |    .598719   .3032042     1.97   0.048     .0044496    1.192988
         19  |   .5915875   .3021274     1.96   0.050    -.0005714    1.183746
         20  |   .5844255   .3009499     1.94   0.052    -.0054255    1.174276
         21  |   .5772353   .2996734     1.93   0.054    -.0101138    1.164584
         22  |   .5700193   .2982998     1.91   0.056    -.0146375    1.154676
         23  |   .5627798   .2968309     1.90   0.058    -.0189981    1.144558
         24  |   .5555193   .2952689     1.88   0.060    -.0231972    1.134236
         25  |     .54824   .2936159     1.87   0.062    -.0272365    1.123717
         26  |   .5409446   .2918741     1.85   0.064    -.0311182    1.113007
         27  |   .5336353   .2900459     1.84   0.066    -.0348443    1.102115
         28  |   .5263146   .2881337     1.83   0.068    -.0384171    1.091046
         29  |   .5189851   .2861401     1.81   0.070    -.0418392    1.079809
         30  |   .5116491   .2840676     1.80   0.072    -.0451132    1.068411
         31  |   .5043091   .2819189     1.79   0.074    -.0482418     1.05686
         32  |   .4969678   .2796968     1.78   0.076    -.0512279    1.045163
         33  |   .4896274   .2774041     1.77   0.078    -.0540746    1.033329
         34  |   .4822906   .2750436     1.75   0.080    -.0567849    1.021366
         35  |   .4749597   .2726183     1.74   0.081    -.0593622    1.009282
         36  |   .4676373   .2701311     1.73   0.083    -.0618099    .9970845
         37  |   .4603259    .267585     1.72   0.085    -.0641312    .9847829
         38  |   .4530278   .2649832     1.71   0.087    -.0663297    .9723854
         39  |   .4457456   .2623287     1.70   0.089    -.0684091    .9599003
         40  |   .4384816   .2596245     1.69   0.091     -.070373    .9473362
         41  |   .4312383   .2568738     1.68   0.093     -.072225    .9347017
         42  |   .4240181   .2540797     1.67   0.095    -.0739689     .922005
         43  |   .4168232   .2512453     1.66   0.097    -.0756085     .909255
         44  |   .4096562   .2483738     1.65   0.099    -.0771475    .8964598
         45  |   .4025191   .2454683     1.64   0.101    -.0785898    .8836281
         46  |   .3954145   .2425318     1.63   0.103    -.0799392    .8707681
         47  |   .3883444   .2395676     1.62   0.105    -.0811994    .8578882
         48  |   .3813111   .2365785     1.61   0.107    -.0823742    .8449964
         49  |   .3743168   .2335677     1.60   0.109    -.0834674     .832101
         50  |   .3673636   .2305381     1.59   0.111    -.0844826    .8192099
         51  |   .3604537   .2274926     1.58   0.113    -.0854236     .806331
         52  |    .353589   .2244342     1.58   0.115    -.0862939     .793472
         53  |   .3467716   .2213657     1.57   0.117    -.0870971    .7806404
         54  |   .3400035   .2182898     1.56   0.119    -.0878366    .7678437
         55  |   .3332866   .2152093     1.55   0.121    -.0885159     .755089
         56  |   .3266227   .2121268     1.54   0.124    -.0891381    .7423835
         57  |   .3200136   .2090448     1.53   0.126    -.0897066    .7297339
         58  |   .3134612   .2059658     1.52   0.128    -.0902245    .7171468
         59  |   .3069671   .2028923     1.51   0.130    -.0906946    .7046288
         60  |   .3005331   .1998266     1.50   0.133    -.0911199     .692186
         61  |   .2941606   .1967709     1.49   0.135    -.0915032    .6798244
         62  |   .2878513   .1937272     1.49   0.137     -.091847    .6675497
         63  |   .2816067   .1906977     1.48   0.140    -.0921539    .6553673
         64  |   .2754281   .1876843     1.47   0.142    -.0924262    .6432825
         65  |    .269317   .1846887     1.46   0.145    -.0926662    .6313003
         66  |   .2632747   .1817128     1.45   0.147    -.0928759    .6194253
         67  |   .2573023   .1787582     1.44   0.150    -.0930573    .6076619
         68  |   .2514011   .1758264     1.43   0.153    -.0932122    .5960145
         69  |   .2455723   .1729187     1.42   0.156    -.0933422    .5844868
         70  |   .2398168   .1700366     1.41   0.158    -.0934488    .5730824
         71  |   .2341357   .1671812     1.40   0.161    -.0935335    .5618049
         72  |     .22853   .1643537     1.39   0.164    -.0935973    .5506572
         73  |   .2230004   .1615549     1.38   0.167    -.0936414    .5396422
         74  |   .2175478   .1587859     1.37   0.171    -.0936667    .5287624
         75  |    .212173   .1560473     1.36   0.174    -.0936741    .5180202
         76  |   .2068767     .15334     1.35   0.177    -.0936641    .5074175
         77  |   .2016594   .1506644     1.34   0.181    -.0936374    .4969562
         78  |   .1965217   .1480211     1.33   0.184    -.0935943    .4866378
         79  |   .1914642   .1454105     1.32   0.188    -.0935352    .4764635
         80  |   .1864871   .1428329     1.31   0.192    -.0934602    .4664345
         81  |   .1815911   .1402885     1.29   0.196    -.0933694    .4565515
         82  |   .1767762   .1377775     1.28   0.199    -.0932627    .4468152
         83  |   .1720429      .1353     1.27   0.204    -.0931402    .4372259
         84  |   .1673912   .1328559     1.26   0.208    -.0930015    .4277839
         85  |   .1628214   .1304452     1.25   0.212    -.0928464    .4184893
         86  |   .1583336   .1280677     1.24   0.216    -.0926745    .4093416
         87  |   .1539276   .1257233     1.22   0.221    -.0924855    .4003408
         88  |   .1496036   .1234117     1.21   0.225    -.0922789    .3914861
         89  |   .1453613   .1211326     1.20   0.230    -.0920542    .3827769
         90  |   .1412008   .1188857     1.19   0.235    -.0918109    .3742125
         91  |   .1371218   .1166706     1.18   0.240    -.0915483    .3657919
         92  |    .133124   .1144868     1.16   0.245     -.091266     .357514
         93  |   .1292071   .1123339     1.15   0.250    -.0909633    .3493776
         94  |   .1253709   .1102115     1.14   0.255    -.0906397    .3413815
         95  |   .1216149    .108119     1.12   0.261    -.0902945    .3335242
         96  |   .1179387   .1060559     1.11   0.266    -.0899271    .3258045
         97  |   .1143418   .1040218     1.10   0.272    -.0895372    .3182207
         98  |   .1108237    .102016     1.09   0.277     -.089124    .3107714
         99  |   .1073839    .100038     1.07   0.283    -.0886871    .3034548
        100  |   .1040217   .0980874     1.06   0.289     -.088226    .2962694
        101  |   .1007365   .0961634     1.05   0.295    -.0877404    .2892133
        102  |   .0975276   .0942657     1.03   0.301    -.0872299     .282285
        103  |   .0943943   .0923937     1.02   0.307    -.0866941    .2754827
        104  |   .0913359   .0905469     1.01   0.313    -.0861328    .2688046
        105  |   .0883516   .0887248     1.00   0.319    -.0855458     .262249
        106  |   .0854405   .0869269     0.98   0.326     -.084933    .2558141
        107  |   .0826019   .0851527     0.97   0.332    -.0842944    .2494982
        108  |   .0798349   .0834019     0.96   0.338    -.0836298    .2432995
        109  |   .0771385   .0816739     0.94   0.345    -.0829394    .2372164
        110  |   .0745119   .0799685     0.93   0.351    -.0822234    .2312472
        111  |   .0719542   .0782851     0.92   0.358    -.0814818    .2253902
        112  |   .0694643   .0766235     0.91   0.365    -.0807151    .2196436
        113  |   .0670413   .0749834     0.89   0.371    -.0799235     .214006
        114  |   .0646842   .0733644     0.88   0.378    -.0791074    .2084758
        115  |   .0623919   .0717663     0.87   0.385    -.0782674    .2030513
        116  |   .0601635   .0701888     0.86   0.391    -.0774039     .197731
        117  |   .0579979   .0686316     0.85   0.398    -.0765176    .1925135
        118  |   .0558941   .0670947     0.83   0.405    -.0756091    .1873973
        119  |   .0538509   .0655778     0.82   0.412    -.0746792     .182381
        120  |   .0518673   .0640807     0.81   0.418    -.0737285    .1774631
        121  |   .0499422   .0626033     0.80   0.425     -.072758    .1726424
        122  |   .0480745   .0611455     0.79   0.432    -.0717684    .1679175
        123  |   .0462632   .0597072     0.77   0.438    -.0707608    .1632871
        124  |    .044507   .0582883     0.76   0.445     -.069736      .15875
        125  |    .042805   .0568888     0.75   0.452     -.068695     .154305
        126  |    .041156   .0555086     0.74   0.458    -.0676388    .1499507
        127  |   .0395588   .0541476     0.73   0.465    -.0665685    .1456862
        128  |   .0380125   .0528059     0.72   0.472    -.0654852    .1415101
        129  |   .0365158   .0514834     0.71   0.478    -.0643899    .1374214
        130  |   .0350676   .0501802     0.70   0.485    -.0632838    .1334191
        131  |    .033667   .0488962     0.69   0.491    -.0621679    .1295019
        132  |   .0323127   .0476315     0.68   0.498    -.0610434    .1256688
        133  |   .0310037   .0463861     0.67   0.504    -.0599114    .1219188
        134  |   .0297388     .04516     0.66   0.510    -.0587732    .1182509
        135  |   .0285171   .0439533     0.65   0.516    -.0576297     .114664
        136  |   .0273375   .0427659     0.64   0.523    -.0564821    .1111571
        137  |   .0261988   .0415979     0.63   0.529    -.0553316    .1077292
        138  |      .0251   .0404494     0.62   0.535    -.0541793    .1043794
        139  |   .0240402   .0393203     0.61   0.541    -.0530263    .1011066
        140  |   .0230182   .0382108     0.60   0.547    -.0518736      .09791
        141  |    .022033   .0371208     0.59   0.553    -.0507224    .0947884
        142  |   .0210837   .0360503     0.58   0.559    -.0495736    .0917409
        143  |   .0201692   .0349993     0.58   0.564    -.0484283    .0887666
        144  |   .0192886    .033968     0.57   0.570    -.0472874    .0858645
        145  |   .0184408   .0329561     0.56   0.576    -.0461521    .0830337
        146  |    .017625   .0319639     0.55   0.581    -.0450231    .0802731
        147  |   .0168402   .0309912     0.54   0.587    -.0439014    .0775818
        148  |   .0160855    .030038     0.54   0.592    -.0427879    .0749589
        149  |     .01536   .0291043     0.53   0.598    -.0416834    .0724033
        150  |   .0146627     .02819     0.52   0.603    -.0405887    .0699141
        151  |   .0139929   .0272951     0.51   0.608    -.0395046    .0674904
        152  |   .0206054   .0538159     0.38   0.702    -.0848718    .1260826
        153  |   .0197086   .0515984     0.38   0.702    -.0814225    .1208396
        154  |   .0188451   .0494568     0.38   0.703    -.0780884    .1157786
        155  |    .018014   .0473892     0.38   0.704    -.0748671    .1108952
        156  |   .0172144   .0453939     0.38   0.705    -.0717559    .1061847
        157  |   .0164453    .043469     0.38   0.705    -.0687524     .101643
        158  |   .0157059   .0416129     0.38   0.706    -.0658539    .0972656
        159  |   .0149951   .0398237     0.38   0.707    -.0630579    .0930481
        160  |   .0143121   .0380997     0.38   0.707    -.0603619    .0889862
        161  |   .0136562   .0364391     0.37   0.708    -.0577632    .0850755
        162  |   .0130263   .0348403     0.37   0.708    -.0552594     .081312
        163  |   .0124217   .0333014     0.37   0.709    -.0528479    .0776913
        164  |   .0118415   .0318209     0.37   0.710    -.0505262    .0742093
        165  |    .011285   .0303969     0.37   0.710    -.0482919     .070862
        166  |   .0107514    .029028     0.37   0.711    -.0461424    .0676452
        167  |   .0102399   .0277124     0.37   0.712    -.0440753    .0645551
        168  |   .0097497   .0264484     0.37   0.712    -.0420882    .0615877
        169  |   .0092802   .0252346     0.37   0.713    -.0401787    .0587392
        170  |   .0088306   .0240694     0.37   0.714    -.0383445    .0560057
        171  |   .0084002   .0229511     0.37   0.714    -.0365833    .0533836
        172  |   .0079883   .0218784     0.37   0.715    -.0348927    .0508692
        173  |   .0075942   .0208497     0.36   0.716    -.0332705    .0484589
        174  |   .0072174   .0198636     0.36   0.716    -.0317145    .0461493
        175  |   .0068572   .0189186     0.36   0.717    -.0302225    .0439369
        176  |   .0065129   .0180133     0.36   0.718    -.0287925    .0418184
        177  |   .0061841   .0171464     0.36   0.718    -.0274223    .0397904
        178  |     .00587   .0163166     0.36   0.719    -.0261099    .0378498
        179  |   .0055701   .0155224     0.36   0.720    -.0248532    .0359935
        180  |    .005284   .0147627     0.36   0.720    -.0236504    .0342184
        181  |   .0050109   .0140362     0.36   0.721    -.0224995    .0325214
        182  |   .0047506   .0133417     0.36   0.722    -.0213987    .0308998
        183  |   .0045023    .012678     0.36   0.722    -.0203461    .0293507
        184  |   .0042657   .0120439     0.35   0.723    -.0193399    .0278714
        185  |   .0040403   .0114384     0.35   0.724    -.0183785    .0264591
        186  |   .0038256   .0108602     0.35   0.725    -.0174601    .0251113
        187  |   .0036212   .0103085     0.35   0.725    -.0165831    .0238255
        188  |   .0034267   .0097821     0.35   0.726    -.0157459    .0225992
        189  |   .0032415     .00928     0.35   0.727    -.0149469      .02143
        190  |   .0030655   .0088013     0.35   0.728    -.0141848    .0203157
        191  |   .0028981    .008345     0.35   0.728    -.0134579     .019254
        192  |   .0027389   .0079103     0.35   0.729    -.0127649    .0182428
        193  |   .0025878   .0074961     0.35   0.730    -.0121044    .0172799
        194  |   .0024441   .0071018     0.34   0.731     -.011475    .0163633
        195  |   .0023078   .0067263     0.34   0.732    -.0108756    .0154912
        196  |   .0021784   .0063691     0.34   0.732    -.0103048    .0146615
        197  |   .0020555   .0060292     0.34   0.733    -.0097615    .0138725
        198  |    .001939   .0057059     0.34   0.734    -.0092444    .0131225
        199  |   .0018286   .0053986     0.34   0.735    -.0087525    .0124096
        200  |   .0017238   .0051065     0.34   0.736    -.0082846    .0117323
        201  |   .0016246   .0048289     0.34   0.737    -.0078398     .011089
        202  |   .0015306   .0045652     0.34   0.737     -.007417    .0104782
        203  |   .0014416   .0043148     0.33   0.738    -.0070152    .0098984
        204  |   .0013573   .0040771     0.33   0.739    -.0066336    .0093482
        205  |   .0012776   .0038514     0.33   0.740    -.0062711    .0088263
        206  |   .0012021   .0036374     0.33   0.741     -.005927    .0083313
        207  |   .0011308   .0034343     0.33   0.742    -.0056003     .007862
        208  |   .0010634   .0032418     0.33   0.743    -.0052904    .0074172
        209  |   .0009996   .0030593     0.33   0.744    -.0049964    .0069957
        210  |   .0009394   .0028863     0.33   0.745    -.0047176    .0065964
        211  |   .0008826   .0027224     0.32   0.746    -.0044532    .0062183
        212  |   .0008289   .0025671     0.32   0.747    -.0042026    .0058604
        213  |   .0007782   .0024201     0.32   0.748    -.0039652    .0055216
        214  |   .0007304    .002281     0.32   0.749    -.0037402    .0052011
        215  |   .0006853   .0021493     0.32   0.750    -.0035272    .0048979
        216  |   .0006428   .0020247     0.32   0.751    -.0033255    .0046112
        217  |   .0006028   .0019068     0.32   0.752    -.0031345    .0043401
        218  |    .000565   .0017954     0.31   0.753    -.0029539    .0040839
        219  |   .0005295     .00169     0.31   0.754    -.0027829    .0038419
        220  |    .000496   .0015905     0.31   0.755    -.0026212    .0036133
        221  |   .0004645   .0014964     0.31   0.756    -.0024683    .0033974
        222  |   .0004349   .0014075     0.31   0.757    -.0023238    .0031936
        223  |    .000407   .0013236     0.31   0.758    -.0021872    .0030012
        224  |   .0003808   .0012444     0.31   0.760    -.0020581    .0028198
        225  |   .0003562   .0011696     0.30   0.761    -.0019362    .0026486
        226  |    .000333    .001099     0.30   0.762    -.0018211    .0024871
        227  |   .0003113   .0010325     0.30   0.763    -.0017124    .0023349
        228  |   .0002909   .0009697     0.30   0.764    -.0016097    .0021915
        229  |   .0002717   .0009105     0.30   0.765    -.0015129    .0020563
        230  |   .0002537   .0008548     0.30   0.767    -.0014216     .001929
        231  |   .0002369   .0008022     0.30   0.768    -.0013354    .0018091
        232  |    .000221   .0007527     0.29   0.769    -.0012541    .0016962
        233  |   .0002062    .000706     0.29   0.770    -.0011775      .00159
        234  |   .0001923   .0006621     0.29   0.771    -.0011054      .00149
        235  |   .0001793   .0006207     0.29   0.773    -.0010373    .0013959
        236  |   .0001671   .0005818     0.29   0.774    -.0009733    .0013075
        237  |   .0001557   .0005452     0.29   0.775    -.0009129    .0012243
        238  |    .000145   .0005108     0.28   0.776    -.0008561    .0011462
        239  |    .000135   .0004784     0.28   0.778    -.0008026    .0010727
        240  |   .0001257    .000448     0.28   0.779    -.0007523    .0010037
        241  |    .000117   .0004193     0.28   0.780    -.0007049    .0009389
        242  |   .0001088   .0003925     0.28   0.782    -.0006604     .000878
        243  |   .0001012   .0003672     0.28   0.783    -.0006185    .0008209
        244  |   .0000941   .0003435     0.27   0.784    -.0005791    .0007673
        245  |   .0000874   .0003212     0.27   0.785    -.0005421     .000717
        246  |   .0000812   .0003003     0.27   0.787    -.0005073    .0006698
        247  |   .0000754   .0002807     0.27   0.788    -.0004747    .0006255
        248  |     .00007   .0002623     0.27   0.789     -.000444    .0005841
        249  |    .000065    .000245     0.27   0.791    -.0004152    .0005452
        250  |   .0000603   .0002288     0.26   0.792    -.0003882    .0005088
        251  |   .0000559   .0002136     0.26   0.793    -.0003628    .0004747
        252  |   .0000519   .0001994     0.26   0.795     -.000339    .0004427
        253  |   .0000481   .0001861     0.26   0.796    -.0003166    .0004128
        254  |   .0000446   .0001736     0.26   0.797    -.0002957    .0003848
        255  |   .0000413   .0001619     0.25   0.799    -.0002761    .0003586
        256  |   .0000382    .000151     0.25   0.800    -.0002577    .0003341
        257  |   .0000354   .0001407     0.25   0.801    -.0002405    .0003112
        258  |   .0000328   .0001312     0.25   0.803    -.0002243    .0002898
        259  |   .0000303   .0001222     0.25   0.804    -.0002092    .0002698
        260  |    .000028   .0001138     0.25   0.806     -.000195    .0002511
        261  |   .0000259    .000106     0.24   0.807    -.0001818    .0002336
        262  |   .0000239   .0000987     0.24   0.808    -.0001694    .0002173
        263  |   .0000221   .0000918     0.24   0.810    -.0001578    .0002021
        264  |   .0000204   .0000854     0.24   0.811     -.000147    .0001878
        265  |   .0000189   .0000794     0.24   0.812    -.0001368    .0001746
        266  |   .0000174   .0000739     0.24   0.814    -.0001274    .0001622
        267  |   .0000161   .0000687     0.23   0.815    -.0001185    .0001507
        268  |   .0000148   .0000638     0.23   0.816    -.0001102    .0001399
        269  |   .0000137   .0000593     0.23   0.818    -.0001025    .0001299
        270  |   .0000126   .0000551     0.23   0.819    -.0000953    .0001205
        271  |   .0000116   .0000511     0.23   0.820    -.0000886    .0001118
        272  |   .0000107   .0000475     0.23   0.822    -.0000823    .0001037
        273  |   9.86e-06    .000044     0.22   0.823    -.0000765    .0000962
        274  |   9.08e-06   .0000409     0.22   0.824     -.000071    .0000892
        275  |   8.35e-06   .0000379     0.22   0.826    -.0000659    .0000826
        276  |   7.69e-06   .0000351     0.22   0.827    -.0000612    .0000765
        277  |   7.07e-06   .0000326     0.22   0.828    -.0000568    .0000709
        278  |   6.50e-06   .0000302     0.22   0.829    -.0000526    .0000656
        279  |   5.97e-06   .0000279     0.21   0.831    -.0000488    .0000608
        280  |   5.49e-06   .0000259     0.21   0.832    -.0000452    .0000562
        281  |   5.04e-06    .000024     0.21   0.833    -.0000419     .000052
        282  |   4.63e-06   .0000222     0.21   0.835    -.0000388    .0000481
        283  |   4.25e-06   .0000205     0.21   0.836     -.000036    .0000445
        284  |   3.90e-06    .000019     0.21   0.837    -.0000333    .0000411
        285  |   3.58e-06   .0000175     0.20   0.838    -.0000308     .000038
        286  |   3.28e-06   .0000162     0.20   0.840    -.0000285    .0000351
        287  |   3.01e-06    .000015     0.20   0.841    -.0000264    .0000324
        288  |   2.76e-06   .0000138     0.20   0.842    -.0000244    .0000299
        289  |   2.53e-06   .0000128     0.20   0.843    -.0000225    .0000276
        290  |   2.31e-06   .0000118     0.20   0.845    -.0000208    .0000255
        291  |   2.12e-06   .0000109     0.19   0.846    -.0000192    .0000235
        292  |   1.94e-06   .0000101     0.19   0.847    -.0000178    .0000216
        293  |   1.77e-06   9.27e-06     0.19   0.848    -.0000164    .0000199
        294  |   1.62e-06   8.55e-06     0.19   0.849    -.0000151    .0000184
        295  |   1.48e-06   7.88e-06     0.19   0.851     -.000014    .0000169
        296  |   1.36e-06   7.26e-06     0.19   0.852    -.0000129    .0000156
        297  |   1.24e-06   6.69e-06     0.19   0.853    -.0000119    .0000144
        298  |   1.13e-06   6.16e-06     0.18   0.854    -.0000109    .0000132
        299  |   1.03e-06   5.67e-06     0.18   0.855    -.0000101    .0000122
        300  |   9.44e-07   5.22e-06     0.18   0.856    -9.29e-06    .0000112
        301  |   8.62e-07   4.80e-06     0.18   0.858    -8.55e-06    .0000103
        302  |   7.86e-07   4.42e-06     0.18   0.859    -7.87e-06    9.44e-06
------------------------------------------------------------------------------

. marginsplot, ///
> scheme(s1mono) graphregion(fcolor(white) ilcolor(white) lcolor(white))

  Variables that uniquely identify margins: att sex

. 
. *Heckman Model Overreport (Model 4)
. heckprobit over_report ib1.sex c.age ib1.lang_d ib1.party_gr c.prof c.att c.i
> nt_count_d, select(survey=ib1.sex c.age ib1.lang_d ib1.party_gr)

Fitting probit model:

Iteration 0:   log likelihood = -69.169746  
Iteration 1:   log likelihood = -59.807742  
Iteration 2:   log likelihood = -59.715883  
Iteration 3:   log likelihood = -59.715771  
Iteration 4:   log likelihood = -59.715771  

Fitting selection model:

Iteration 0:   log likelihood = -164.13381  
Iteration 1:   log likelihood = -160.27548  
Iteration 2:   log likelihood = -160.27347  
Iteration 3:   log likelihood = -160.27347  

Comparison:    log likelihood = -219.98924

Fitting starting values:

Iteration 0:   log likelihood = -73.473601  
Iteration 1:   log likelihood =   -57.3356  
Iteration 2:   log likelihood = -57.198006  
Iteration 3:   log likelihood = -57.197973  
Iteration 4:   log likelihood = -57.197973  

Fitting full model:

initial values not feasible
note:  default initial values infeasible; starting from B=0

Iteration 0:   log likelihood = -239.13578  (not concave)
Iteration 1:   log likelihood =   -227.047  (not concave)
Iteration 2:   log likelihood = -222.24724  (not concave)
Iteration 3:   log likelihood =  -221.5838  (not concave)
Iteration 4:   log likelihood = -221.23454  (not concave)
Iteration 5:   log likelihood = -220.92339  (not concave)
Iteration 6:   log likelihood = -220.76794  (not concave)
Iteration 7:   log likelihood = -220.60637  (not concave)
Iteration 8:   log likelihood = -220.52965  (not concave)
Iteration 9:   log likelihood = -220.45064  (not concave)
Iteration 10:  log likelihood = -220.40227  
Iteration 11:  log likelihood = -220.34774  
Iteration 12:  log likelihood = -219.82818  (not concave)
Iteration 13:  log likelihood = -219.82354  (not concave)
Iteration 14:  log likelihood = -219.81915  (not concave)
Iteration 15:  log likelihood = -219.78902  (not concave)
Iteration 16:  log likelihood = -219.74248  (not concave)
Iteration 17:  log likelihood =  -219.7329  (not concave)
Iteration 18:  log likelihood = -219.72551  (not concave)
Iteration 19:  log likelihood = -219.71867  (not concave)
Iteration 20:  log likelihood = -219.70828  (not concave)
Iteration 21:  log likelihood = -219.69754  (not concave)
Iteration 22:  log likelihood = -219.46012  (not concave)
Iteration 23:  log likelihood = -219.31816  
Iteration 24:  log likelihood = -219.28707  
Iteration 25:  log likelihood =  -219.0232  
Iteration 26:  log likelihood = -218.92904  
Iteration 27:  log likelihood = -218.92211  
Iteration 28:  log likelihood = -218.91981  
Iteration 29:  log likelihood = -218.91745  
Iteration 30:  log likelihood = -218.91736  
Iteration 31:  log likelihood = -218.91725  (not concave)
Iteration 32:  log likelihood = -218.91708  
Iteration 33:  log likelihood = -218.91707  
Iteration 34:  log likelihood = -218.91706  
Iteration 35:  log likelihood = -218.91704  (not concave)
Iteration 36:  log likelihood = -218.91704  (not concave)
Iteration 37:  log likelihood = -218.91704  
Iteration 38:  log likelihood = -218.91704  
Iteration 39:  log likelihood = -218.91704  (not concave)
Iteration 40:  log likelihood = -218.91704  (backed up)
Iteration 41:  log likelihood = -218.91704  
Iteration 42:  log likelihood = -218.91704  (backed up)
Iteration 43:  log likelihood = -218.91704  
Iteration 44:  log likelihood = -218.91704  (not concave)
Iteration 45:  log likelihood = -218.91704  
Iteration 46:  log likelihood = -218.91704  (backed up)
Iteration 47:  log likelihood = -218.91704  (not concave)
Iteration 48:  log likelihood = -218.91704  (backed up)
Iteration 49:  log likelihood = -218.91704  (not concave)
Iteration 50:  log likelihood = -218.91704  (not concave)
Iteration 51:  log likelihood = -218.91704  (not concave)
Iteration 52:  log likelihood = -218.91704  
Iteration 53:  log likelihood = -218.91704  (not concave)
Iteration 54:  log likelihood = -218.91704  (not concave)
Iteration 55:  log likelihood = -218.91704  (not concave)
Iteration 56:  log likelihood = -218.91704  (not concave)
Iteration 57:  log likelihood = -218.91704  (not concave)
Iteration 58:  log likelihood = -218.91704  
Iteration 59:  log likelihood = -218.91704  (backed up)
Iteration 60:  log likelihood = -218.91704  (backed up)
Iteration 61:  log likelihood = -218.91704  (not concave)
Iteration 62:  log likelihood = -218.91704  (backed up)
Iteration 63:  log likelihood = -218.91704  (not concave)
Iteration 64:  log likelihood = -218.91704  (backed up)
Iteration 65:  log likelihood = -218.91704  (backed up)
Iteration 66:  log likelihood = -218.91704  (backed up)
Iteration 67:  log likelihood = -218.91704  (not concave)
Iteration 68:  log likelihood = -218.91704  (not concave)
Iteration 69:  log likelihood = -218.91704  (backed up)
Iteration 70:  log likelihood = -218.91704  (not concave)
Iteration 71:  log likelihood = -218.91704  (not concave)
Iteration 72:  log likelihood = -218.91704  (not concave)
Iteration 73:  log likelihood = -218.91704  (not concave)
Iteration 74:  log likelihood = -218.91704  
Iteration 75:  log likelihood = -218.91704  (backed up)
Iteration 76:  log likelihood = -218.91704  (backed up)
Iteration 77:  log likelihood = -218.91704  (backed up)
Iteration 78:  log likelihood = -218.91704  
Iteration 79:  log likelihood = -218.91704  (backed up)
Iteration 80:  log likelihood = -218.91704  (not concave)
Iteration 81:  log likelihood = -218.91704  (not concave)
Iteration 82:  log likelihood = -218.91704  (backed up)
Iteration 83:  log likelihood = -218.91704  
Iteration 84:  log likelihood = -218.91704  (backed up)
Iteration 85:  log likelihood = -218.91704  (not concave)
Iteration 86:  log likelihood = -218.91704  (not concave)
Iteration 87:  log likelihood = -218.91704  
Iteration 88:  log likelihood = -218.91704  (not concave)
Iteration 89:  log likelihood = -218.91704  (backed up)
Iteration 90:  log likelihood = -218.91704  (backed up)
Iteration 91:  log likelihood = -218.91704  
Iteration 92:  log likelihood = -218.91704  (not concave)
Iteration 93:  log likelihood = -218.91704  (backed up)
Iteration 94:  log likelihood = -218.91704  (backed up)
Iteration 95:  log likelihood = -218.91704  (backed up)
Iteration 96:  log likelihood = -218.91704  (backed up)
Iteration 97:  log likelihood = -218.91704  (backed up)
Iteration 98:  log likelihood = -218.91704  (backed up)
Iteration 99:  log likelihood = -218.91704  
Iteration 100: log likelihood = -218.91704  (not concave)
Iteration 101: log likelihood = -218.91704  (backed up)
Iteration 102: log likelihood = -218.91704  (not concave)
Iteration 103: log likelihood = -218.91704  
Iteration 104: log likelihood = -218.91704  (not concave)
Iteration 105: log likelihood = -218.91704  (not concave)
Iteration 106: log likelihood = -218.91704  (backed up)
Iteration 107: log likelihood = -218.91704  (backed up)
Iteration 108: log likelihood = -218.91704  (backed up)
Iteration 109: log likelihood = -218.91704  (backed up)
Iteration 110: log likelihood = -218.91704  (backed up)
Iteration 111: log likelihood = -218.91704  (not concave)
Iteration 112: log likelihood = -218.91704  (not concave)
Iteration 113: log likelihood = -218.91704  (not concave)
Iteration 114: log likelihood = -218.91704  (not concave)
Iteration 115: log likelihood = -218.91704  (backed up)
Iteration 116: log likelihood = -218.91704  (backed up)
Iteration 117: log likelihood = -218.91704  (not concave)
Iteration 118: log likelihood = -218.91704  (not concave)
Iteration 119: log likelihood = -218.91704  (backed up)
Iteration 120: log likelihood = -218.91704  (backed up)
Iteration 121: log likelihood = -218.91704  (backed up)
Iteration 122: log likelihood = -218.91704  (backed up)
Iteration 123: log likelihood = -218.91704  (not concave)
Iteration 124: log likelihood = -218.91704  (not concave)
Iteration 125: log likelihood = -218.91704  (backed up)
Iteration 126: log likelihood = -218.91704  (not concave)
Iteration 127: log likelihood = -218.91704  
Iteration 128: log likelihood = -218.91704  (backed up)
Iteration 129: log likelihood = -218.91704  (backed up)
Iteration 130: log likelihood = -218.91704  
Iteration 131: log likelihood = -218.91704  (not concave)
Iteration 132: log likelihood = -218.91704  (not concave)
Iteration 133: log likelihood = -218.91704  
Iteration 134: log likelihood = -218.91704  (not concave)
Iteration 135: log likelihood = -218.91704  (not concave)
Iteration 136: log likelihood = -218.91704  (not concave)
Iteration 137: log likelihood = -218.91704  (not concave)
Iteration 138: log likelihood = -218.91704  (not concave)
Iteration 139: log likelihood = -218.91704  (backed up)
Iteration 140: log likelihood = -218.91704  (not concave)
Iteration 141: log likelihood = -218.91704  (backed up)
Iteration 142: log likelihood = -218.91704  
Iteration 143: log likelihood = -218.91704  (backed up)
Iteration 144: log likelihood = -218.91704  (backed up)
Iteration 145: log likelihood = -218.91704  (backed up)
Iteration 146: log likelihood = -218.91704  (not concave)
Iteration 147: log likelihood = -218.91704  (not concave)
Iteration 148: log likelihood = -218.91704  
Iteration 149: log likelihood = -218.91704  (not concave)
Iteration 150: log likelihood = -218.91704  
Iteration 151: log likelihood = -218.91704  (not concave)
Iteration 152: log likelihood = -218.91704  (backed up)
Iteration 153: log likelihood = -218.91704  (backed up)
Iteration 154: log likelihood = -218.91704  (not concave)
Iteration 155: log likelihood = -218.91704  
Iteration 156: log likelihood = -218.91704  (not concave)
Iteration 157: log likelihood = -218.91704  
Iteration 158: log likelihood = -218.91704  (not concave)
Iteration 159: log likelihood = -218.91704  (not concave)
Iteration 160: log likelihood = -218.91704  
Iteration 161: log likelihood = -218.91704  (not concave)
Iteration 162: log likelihood = -218.91704  (backed up)
Iteration 163: log likelihood = -218.91704  (backed up)
Iteration 164: log likelihood = -218.91704  (backed up)
Iteration 165: log likelihood = -218.91704  (backed up)
Iteration 166: log likelihood = -218.91704  (backed up)
Iteration 167: log likelihood = -218.91704  (backed up)
Iteration 168: log likelihood = -218.91704  (not concave)
Iteration 169: log likelihood = -218.91704  
Iteration 170: log likelihood = -218.91704  (backed up)
Iteration 171: log likelihood = -218.91704  (backed up)
Iteration 172: log likelihood = -218.91704  (not concave)
Iteration 173: log likelihood = -218.91704  (not concave)
Iteration 174: log likelihood = -218.91704  
Iteration 175: log likelihood = -218.91704  (backed up)
Iteration 176: log likelihood = -218.91704  (not concave)
Iteration 177: log likelihood = -218.91704  (backed up)
Iteration 178: log likelihood = -218.91704  (not concave)
Iteration 179: log likelihood = -218.91704  (not concave)
Iteration 180: log likelihood = -218.91704  (backed up)
Iteration 181: log likelihood = -218.91704  (not concave)
Iteration 182: log likelihood = -218.91704  (not concave)
Iteration 183: log likelihood = -218.91704  (backed up)
Iteration 184: log likelihood = -218.91704  (backed up)
Iteration 185: log likelihood = -218.91704  (backed up)
Iteration 186: log likelihood = -218.91704  (backed up)
Iteration 187: log likelihood = -218.91704  (backed up)
Iteration 188: log likelihood = -218.91704  (not concave)
Iteration 189: log likelihood = -218.91704  (backed up)
Iteration 190: log likelihood = -218.91704  (backed up)
Iteration 191: log likelihood = -218.91704  (backed up)
Iteration 192: log likelihood = -218.91704  (backed up)
Iteration 193: log likelihood = -218.91704  (backed up)
Iteration 194: log likelihood = -218.91704  (not concave)
Iteration 195: log likelihood = -218.91704  (backed up)
Iteration 196: log likelihood = -218.91704  (not concave)
Iteration 197: log likelihood = -218.91704  (backed up)
Iteration 198: log likelihood = -218.91704  (not concave)
Iteration 199: log likelihood = -218.91704  (not concave)
Iteration 200: log likelihood = -218.91704  (backed up)
Iteration 201: log likelihood = -218.91704  (not concave)
Iteration 202: log likelihood = -218.91704  (backed up)
Iteration 203: log likelihood = -218.91704  (backed up)
Iteration 204: log likelihood = -218.91704  (not concave)
Iteration 205: log likelihood = -218.91704  (not concave)
Iteration 206: log likelihood = -218.91704  (backed up)
Iteration 207: log likelihood = -218.91704  (not concave)
Iteration 208: log likelihood = -218.91704  (not concave)
Iteration 209: log likelihood = -218.91704  (backed up)
Iteration 210: log likelihood = -218.91704  (not concave)
Iteration 211: log likelihood = -218.91704  
Iteration 212: log likelihood = -218.91704  (not concave)
Iteration 213: log likelihood = -218.91704  
Iteration 214: log likelihood = -218.91704  (backed up)
Iteration 215: log likelihood = -218.91704  (not concave)
Iteration 216: log likelihood = -218.91704  (not concave)
Iteration 217: log likelihood = -218.91704  (not concave)
Iteration 218: log likelihood = -218.91704  (not concave)
Iteration 219: log likelihood = -218.91704  (not concave)
Iteration 220: log likelihood = -218.91704  
Iteration 221: log likelihood = -218.91704  (not concave)
Iteration 222: log likelihood = -218.91704  (not concave)
Iteration 223: log likelihood = -218.91704  
Iteration 224: log likelihood = -218.91704  (not concave)
Iteration 225: log likelihood = -218.91704  (not concave)
Iteration 226: log likelihood = -218.91704  
Iteration 227: log likelihood = -218.91704  (backed up)
Iteration 228: log likelihood = -218.91704  (backed up)
Iteration 229: log likelihood = -218.91704  (not concave)
Iteration 230: log likelihood = -218.91704  
Iteration 231: log likelihood = -218.91704  (not concave)
Iteration 232: log likelihood = -218.91704  (not concave)
Iteration 233: log likelihood = -218.91704  (not concave)
Iteration 234: log likelihood = -218.91704  (not concave)
Iteration 235: log likelihood = -218.91704  (not concave)
Iteration 236: log likelihood = -218.91704  (not concave)
Iteration 237: log likelihood = -218.91704  (backed up)
Iteration 238: log likelihood = -218.91704  (not concave)
Iteration 239: log likelihood = -218.91704  
Iteration 240: log likelihood = -218.91704  (backed up)
Iteration 241: log likelihood = -218.91704  
Iteration 242: log likelihood = -218.91704  (not concave)
Iteration 243: log likelihood = -218.91704  
Iteration 244: log likelihood = -218.91704  (backed up)
Iteration 245: log likelihood = -218.91704  (not concave)
Iteration 246: log likelihood = -218.91704  
Iteration 247: log likelihood = -218.91704  (not concave)
Iteration 248: log likelihood = -218.91704  (not concave)
Iteration 249: log likelihood = -218.91704  (not concave)
Iteration 250: log likelihood = -218.91704  (not concave)
Iteration 251: log likelihood = -218.91704  (not concave)
Iteration 252: log likelihood = -218.91704  
Iteration 253: log likelihood = -218.91704  (backed up)
Iteration 254: log likelihood = -218.91704  (backed up)
Iteration 255: log likelihood = -218.91704  (backed up)
Iteration 256: log likelihood = -218.91704  (not concave)
Iteration 257: log likelihood = -218.91704  
Iteration 258: log likelihood = -218.91704  (backed up)
Iteration 259: log likelihood = -218.91704  (not concave)
Iteration 260: log likelihood = -218.91704  (not concave)
Iteration 261: log likelihood = -218.91704  (not concave)
Iteration 262: log likelihood = -218.91704  (not concave)
Iteration 263: log likelihood = -218.91704  (not concave)
Iteration 264: log likelihood = -218.91704  (not concave)
Iteration 265: log likelihood = -218.91704  (backed up)
Iteration 266: log likelihood = -218.91704  

Probit model with sample selection              Number of obs      =       239
                                                Censored obs       =       133
                                                Uncensored obs     =       106

                                                Wald chi2(8)       =     18.50
Log likelihood =  -218.917                      Prob > chi2        =    0.0178

------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
over_report  |
         sex |
       male  |  -.0667993   .2026464    -0.33   0.742    -.4639789    .3303804
         age |  -.0064643   .0089762    -0.72   0.471    -.0240573    .0111286
             |
      lang_d |
      latin  |   .0779676   .2059183     0.38   0.705    -.3256249    .4815601
             |
   party_grp |
     center  |  -.0754117   .2408045    -0.31   0.754    -.5473798    .3965564
       left  |  -.2696166    .271981    -0.99   0.322    -.8026896    .2634564
             |
        prof |  -.2161053   .3585072    -0.60   0.547    -.9187666     .486556
         att |   .2510145   .1600857     1.57   0.117    -.0627477    .5647767
 int_count_d |  -.3404519   .1119684    -3.04   0.002     -.559906   -.1209978
       _cons |   .5687294   .7129857     0.80   0.425    -.8286968    1.966156
-------------+----------------------------------------------------------------
survey       |
         sex |
       male  |  -.2456061   .1847458    -1.33   0.184    -.6077013     .116489
         age |   .0053114   .0083667     0.63   0.526     -.011087    .0217097
             |
      lang_d |
      latin  |    .182031   .1861755     0.98   0.328    -.1828662    .5469282
             |
   party_grp |
     center  |   .2396035   .2111574     1.13   0.256    -.1742574    .6534644
       left  |   .4534155   .2323355     1.95   0.051    -.0019537    .9087848
             |
       _cons |  -.5548204   .5005293    -1.11   0.268     -1.53584     .426199
-------------+----------------------------------------------------------------
     /athrho |  -16.06307   1.271083   -12.64   0.000    -18.55435    -13.5718
-------------+----------------------------------------------------------------
         rho |         -1   5.70e-14                            -1          -1
------------------------------------------------------------------------------
LR test of indep. eqns. (rho = 0):   chi2(1) =     2.14   Prob > chi2 = 0.1431

. 
. *Heckman Model Underreport (Model 5)
. heckprobit under_report ib1.sex c.age ib1.lang_d ib1.party_gr c.prof c.att c.
> int_count_d, select(survey=ib1.sex c.age ib1.lang_d)

Fitting probit model:

Iteration 0:   log likelihood = -37.435955  
Iteration 1:   log likelihood = -20.300517  
Iteration 2:   log likelihood = -16.446601  
Iteration 3:   log likelihood = -16.129772  
Iteration 4:   log likelihood =  -16.12692  
Iteration 5:   log likelihood = -16.126918  
Iteration 6:   log likelihood = -16.126918  

Fitting selection model:

Iteration 0:   log likelihood = -164.13381  
Iteration 1:   log likelihood = -161.75173  
Iteration 2:   log likelihood = -161.75137  
Iteration 3:   log likelihood = -161.75137  

Comparison:    log likelihood = -177.87828

Fitting starting values:

Iteration 0:   log likelihood = -73.473601  
Iteration 1:   log likelihood = -19.940452  
Iteration 2:   log likelihood = -16.456293  
Iteration 3:   log likelihood = -16.147217  
Iteration 4:   log likelihood = -16.124854  
Iteration 5:   log likelihood =  -16.12465  
Iteration 6:   log likelihood =  -16.12465  

Fitting full model:

initial values not feasible
note:  default initial values infeasible; starting from B=0

Iteration 0:   log likelihood = -239.13578  (not concave)
Iteration 1:   log likelihood = -197.11825  (not concave)
Iteration 2:   log likelihood = -187.56392  (not concave)
Iteration 3:   log likelihood = -183.11697  (not concave)
Iteration 4:   log likelihood = -181.24732  (not concave)
Iteration 5:   log likelihood = -179.50477  
Iteration 6:   log likelihood = -178.40231  
Iteration 7:   log likelihood = -177.01447  
Iteration 8:   log likelihood = -176.76403  
Iteration 9:   log likelihood = -176.56698  
Iteration 10:  log likelihood = -176.54894  
Iteration 11:  log likelihood = -176.45336  
Iteration 12:  log likelihood = -176.44247  
Iteration 13:  log likelihood = -176.43333  
Iteration 14:  log likelihood = -176.42703  
Iteration 15:  log likelihood = -176.42624  
Iteration 16:  log likelihood = -176.42558  
Iteration 17:  log likelihood = -176.42528  (backed up)
Iteration 18:  log likelihood = -176.42527  (backed up)
Iteration 19:  log likelihood = -176.42447  (backed up)
Iteration 20:  log likelihood =  -176.4242  (backed up)
Iteration 21:  log likelihood = -176.42415  
Iteration 22:  log likelihood = -176.42405  (not concave)
Iteration 23:  log likelihood = -176.42402  
Iteration 24:  log likelihood = -176.42399  (backed up)
Iteration 25:  log likelihood = -176.42397  (not concave)
Iteration 26:  log likelihood = -176.42396  (not concave)
Iteration 27:  log likelihood = -176.42395  (not concave)
Iteration 28:  log likelihood = -176.42394  (not concave)
Iteration 29:  log likelihood = -176.42394  
Iteration 30:  log likelihood = -176.42393  (backed up)
Iteration 31:  log likelihood = -176.42392  (not concave)
Iteration 32:  log likelihood = -176.42392  (not concave)
Iteration 33:  log likelihood = -176.42392  
Iteration 34:  log likelihood = -176.42392  (backed up)
Iteration 35:  log likelihood = -176.42392  (not concave)
Iteration 36:  log likelihood = -176.42392  (not concave)
Iteration 37:  log likelihood = -176.42392  (backed up)
Iteration 38:  log likelihood = -176.42392  (backed up)
Iteration 39:  log likelihood = -176.42392  (not concave)
Iteration 40:  log likelihood = -176.42392  (backed up)

Probit model with sample selection              Number of obs      =       239
                                                Censored obs       =       133
                                                Uncensored obs     =       106

                                                Wald chi2(8)       =     22.16
Log likelihood = -176.4239                      Prob > chi2        =    0.0046

------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
under_report |
         sex |
       male  |   1.617944   .4719715     3.43   0.001     .6928964    2.542991
         age |   -.017296   .0135909    -1.27   0.203    -.0439336    .0093417
             |
      lang_d |
      latin  |  -.3820033   .2549477    -1.50   0.134    -.8816917    .1176851
             |
   party_grp |
     center  |   .2985491   .2033026     1.47   0.142    -.0999168    .6970149
       left  |   .2380511   .1517024     1.57   0.117    -.0592802    .5353823
             |
        prof |   .5072187   1.188513     0.43   0.670    -1.822225    2.836662
         att |   -.374981   .1433971    -2.61   0.009    -.6560341   -.0939279
 int_count_d |   1.033255   .3368478     3.07   0.002     .3730456    1.693465
       _cons |  -.3033294   1.203059    -0.25   0.801    -2.661281    2.054622
-------------+----------------------------------------------------------------
survey       |
         sex |
       male  |  -.3052149   .1800129    -1.70   0.090    -.6580338     .047604
         age |      .0042   .0082201     0.51   0.609    -.0119111     .020311
             |
      lang_d |
      latin  |   .2570239   .1801742     1.43   0.154    -.0961111    .6101589
       _cons |  -.2282379   .4551036    -0.50   0.616    -1.120225    .6637488
-------------+----------------------------------------------------------------
     /athrho |  -14.24519   12.64028    -1.13   0.260    -39.01969     10.5293
-------------+----------------------------------------------------------------
         rho |         -1   2.14e-11                            -1           1
------------------------------------------------------------------------------
LR test of indep. eqns. (rho = 0):   chi2(1) =     2.91   Prob > chi2 = 0.0881

. 
. *Determinates for Reported Evaluation Demand (Model 6)
. probit pr_d i1.sex c.age i0.del_bd c.prof c.att c.seniority_years i1.com_over
>  i1.board

Iteration 0:   log likelihood = -63.810625  
Iteration 1:   log likelihood = -53.578243  
Iteration 2:   log likelihood = -53.420954  
Iteration 3:   log likelihood = -53.420582  
Iteration 4:   log likelihood = -53.420582  

Probit regression                                 Number of obs   =         93
                                                  LR chi2(8)      =      20.78
                                                  Prob > chi2     =     0.0078
Log likelihood = -53.420582                       Pseudo R2       =     0.1628

-------------------------------------------------------------------------------
--
           pr_d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interva
> l]
----------------+--------------------------------------------------------------
--
            sex |
        female  |   .7290901   .3254384     2.24   0.025     .0912426    1.3669
> 38
            age |    .008751   .0150789     0.58   0.562    -.0208031    .03830
> 51
                |
         del_bd |
         agree  |  -.6758551   .4075737    -1.66   0.097    -1.474685    .12297
> 47
           prof |   .0384253   1.002793     0.04   0.969    -1.927013    2.0038
> 63
            att |   .6225814   .2555873     2.44   0.015     .1216396    1.1235
> 23
seniority_years |  -.0247322   .0319211    -0.77   0.438    -.0872965     .0378
> 32
     1.com_over |  -.0311903   .3098641    -0.10   0.920    -.6385128    .57613
> 22
        1.board |  -.2760609   .4938298    -0.56   0.576     -1.24395    .69182
> 78
          _cons |  -2.182509   1.191634    -1.83   0.067    -4.518068    .15304
> 97
-------------------------------------------------------------------------------
--

. 
. *Predicted Probabilities of Reported Evaluation Demand (Figure 4)
. margins sex, at(att=(1(0.02)4) (mean) _all) noatlegend

Adjusted predictions                              Number of obs   =         93
Model VCE    : OIM

Expression   : Pr(pr_d), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     _at#sex |
     1#male  |   .0882023   .0888494     0.99   0.321    -.0859393     .262344
   1#female  |   .2612786   .1979015     1.32   0.187    -.1266011    .6491584
     2#male  |   .0901698   .0895391     1.01   0.314    -.0853236    .2656631
   2#female  |   .2652402   .1979434     1.34   0.180    -.1227218    .6532023
     3#male  |   .0921695   .0902144     1.02   0.307    -.0846476    .2689865
   3#female  |   .2692317   .1979479     1.36   0.174     -.118739    .6572024
     4#male  |   .0942016   .0908751     1.04   0.300    -.0839103    .2723135
   4#female  |   .2732527   .1979147     1.38   0.167    -.1146529    .6611583
     5#male  |   .0962665   .0915205     1.05   0.293    -.0831104    .2756434
   5#female  |   .2773029   .1978439     1.40   0.161     -.110464    .6650697
     6#male  |   .0983643   .0921502     1.07   0.286    -.0822469    .2789754
   6#female  |   .2813817   .1977354     1.42   0.155    -.1061726     .668936
     7#male  |   .1004951   .0927638     1.08   0.279    -.0813185    .2823088
   7#female  |    .285489   .1975894     1.44   0.148    -.1017791    .6727571
     8#male  |   .1026593   .0933607     1.10   0.272    -.0803242    .2856429
   8#female  |   .2896241   .1974058     1.47   0.142    -.0972843    .6765324
     9#male  |    .104857   .0939405     1.12   0.264     -.079263     .288977
   9#female  |   .2937867   .1971848     1.49   0.136    -.0926885    .6802619
    10#male  |   .1070884   .0945028     1.13   0.257    -.0781336    .2923104
  10#female  |   .2979764   .1969265     1.51   0.130    -.0879924    .6839453
    11#male  |   .1093536    .095047     1.15   0.250    -.0769351    .2956423
  11#female  |   .3021927   .1966309     1.54   0.124    -.0831968    .6875823
    12#male  |   .1116529   .0955728     1.17   0.243    -.0756665    .2989722
  12#female  |   .3064352   .1962983     1.56   0.119    -.0783024    .6911728
    13#male  |   .1139863   .0960798     1.19   0.235    -.0743266    .3022992
  13#female  |   .3107033   .1959288     1.59   0.113      -.07331    .6947166
    14#male  |   .1163541   .0965674     1.20   0.228    -.0729146    .3056227
  14#female  |   .3149966   .1955225     1.61   0.107    -.0682205    .6982138
    15#male  |   .1187563   .0970353     1.22   0.221    -.0714294    .3089421
  15#female  |   .3193147   .1950798     1.64   0.102    -.0630347    .7016641
    16#male  |   .1211932   .0974831     1.24   0.214    -.0698701    .3122566
  16#female  |    .323657   .1946009     1.66   0.096    -.0577538    .7050677
    17#male  |   .1236649   .0979103     1.26   0.207    -.0682359    .3155656
  17#female  |    .328023    .194086     1.69   0.091    -.0523786    .7084245
    18#male  |   .1261714   .0983167     1.28   0.199    -.0665257    .3188685
  18#female  |   .3324121   .1935354     1.72   0.086    -.0469103    .7117346
    19#male  |   .1287129   .0987017     1.30   0.192    -.0647388    .3221646
  19#female  |   .3368239   .1929495     1.75   0.081    -.0413502     .714998
    20#male  |   .1312895    .099065     1.33   0.185    -.0628743    .3254533
  20#female  |   .3412579   .1923286     1.77   0.076    -.0356993     .718215
    21#male  |   .1339012   .0994063     1.35   0.178    -.0609315     .328734
  21#female  |   .3457134   .1916731     1.80   0.071    -.0299589    .7213857
    22#male  |   .1365483   .0997252     1.37   0.171    -.0589096    .3320061
  22#female  |   .3501899   .1909832     1.83   0.067    -.0241304    .7245102
    23#male  |   .1392306   .1000214     1.39   0.164    -.0568077     .335269
  23#female  |   .3546869   .1902596     1.86   0.062     -.018215    .7275889
    24#male  |   .1419484   .1002946     1.42   0.157    -.0546254    .3385222
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   137#male  |   .6166862   .0846899     7.28   0.000      .450697    .7826753
 137#female  |   .8411747   .0712321    11.81   0.000     .7015623     .980787
   138#male  |   .6212731   .0856373     7.25   0.000     .4534271    .7891191
 138#female  |   .8440526   .0709061    11.90   0.000     .7050791     .983026
   139#male  |   .6258425    .086586     7.23   0.000     .4561371    .7955479
 139#female  |   .8468955    .070583    12.00   0.000     .7085554    .9852357
   140#male  |   .6303938   .0875345     7.20   0.000     .4588294    .8019581
 140#female  |   .8497037   .0702622    12.09   0.000     .7119924     .987415
   141#male  |   .6349263   .0884812     7.18   0.000     .4615064    .8083462
 141#female  |   .8524769   .0699429    12.19   0.000     .7153913    .9895625
   142#male  |   .6394396   .0894246     7.15   0.000     .4641706    .8147086
 142#female  |   .8552154   .0696247    12.28   0.000     .7187536    .9916772
   143#male  |    .643933   .0903634     7.13   0.000      .466824    .8210421
 143#female  |   .8579191   .0693068    12.38   0.000     .7220802     .993758
   144#male  |    .648406   .0912962     7.10   0.000     .4694687    .8273433
 144#female  |   .8605881   .0689888    12.47   0.000     .7253725    .9958038
   145#male  |   .6528581   .0922217     7.08   0.000      .472107    .8336093
 145#female  |   .8632226   .0686702    12.57   0.000     .7286315    .9978136
   146#male  |   .6572887   .0931385     7.06   0.000     .4747405    .8398369
 146#female  |   .8658225   .0683503    12.67   0.000     .7318583    .9997866
   147#male  |   .6616972   .0940456     7.04   0.000     .4773712    .8460232
 147#female  |   .8683879   .0680288    12.77   0.000      .735054    1.001722
   148#male  |   .6660832   .0949417     7.02   0.000     .4800008    .8521655
 148#female  |    .870919   .0677051    12.86   0.000     .7382195    1.003619
   149#male  |   .6704461   .0958258     7.00   0.000      .482631    .8582611
 149#female  |   .8734159   .0673789    12.96   0.000     .7413557    1.005476
   150#male  |   .6747854   .0966967     6.98   0.000     .4852634    .8643074
 150#female  |   .8758787   .0670497    13.06   0.000     .7444636    1.007294
   151#male  |   .6791007   .0975534     6.96   0.000     .4878995    .8703018
 151#female  |   .8783075   .0667172    13.16   0.000     .7475441    1.009071
------------------------------------------------------------------------------

. marginsplot, ///
> scheme(s1mono) graphregion(fcolor(white) ilcolor(white) lcolor(white))

  Variables that uniquely identify margins: att sex

. 
. *Determinates for Validated Evaluation Demand (Model 7) 
. probit int_count_d i1.sex c.age i0.del_bd c.prof c.att c.seniority_years i1.c
> om_over i1.board if pr_d==0 | pr_d==1 

Iteration 0:   log likelihood = -57.711656  
Iteration 1:   log likelihood = -52.525543  
Iteration 2:   log likelihood = -52.482535  
Iteration 3:   log likelihood = -52.482517  
Iteration 4:   log likelihood = -52.482517  

Probit regression                                 Number of obs   =         93
                                                  LR chi2(8)      =      10.46
                                                  Prob > chi2     =     0.2343
Log likelihood = -52.482517                       Pseudo R2       =     0.0906

-------------------------------------------------------------------------------
--
    int_count_d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interva
> l]
----------------+--------------------------------------------------------------
--
            sex |
        female  |   .1814415   .3099855     0.59   0.558    -.4261188    .78900
> 19
            age |  -.0107488   .0152326    -0.71   0.480     -.040604    .01910
> 65
                |
         del_bd |
         agree  |  -.4950573   .4606494    -1.07   0.283    -1.397914    .40779
> 89
           prof |   1.475993   1.017977     1.45   0.147    -.5192046     3.471
> 19
            att |   .2881196   .2456853     1.17   0.241    -.1934147     .7696
> 54
seniority_years |  -.0080063   .0326191    -0.25   0.806    -.0719386     .0559
> 26
     1.com_over |   .3567302     .30511     1.17   0.242    -.2412745    .95473
> 48
        1.board |   .0180834   .5146363     0.04   0.972    -.9905851    1.0267
> 52
          _cons |  -1.866141    1.19569    -1.56   0.119    -4.209651    .47736
> 85
-------------------------------------------------------------------------------
--

. 
. *Predicted Probabilities of Validated Evaluation Demand (Figure 5)
. margins sex, at(att=(1(0.02)4) (mean) _all) noatlegend

Adjusted predictions                              Number of obs   =         93
Model VCE    : OIM

Expression   : Pr(int_count_d), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     _at#sex |
     1#male  |   .1198215   .1059829     1.13   0.258    -.0879011    .3275441
   1#female  |   .1586491   .1457124     1.09   0.276    -.1269419    .4442401
     2#male  |   .1209416   .1057739     1.14   0.253    -.0863714    .3282546
   2#female  |   .1600037   .1454541     1.10   0.271    -.1250811    .4450885
     3#male  |    .122069   .1055553     1.16   0.247    -.0848155    .3289536
   3#female  |   .1613658   .1451853     1.11   0.266    -.1231921    .4459238
     4#male  |   .1232038   .1053271     1.17   0.242    -.0832334     .329641
   4#female  |   .1627355    .144906     1.12   0.261    -.1212751     .446746
     5#male  |   .1243459   .1050892     1.18   0.237    -.0816251    .3303169
   5#female  |   .1641126   .1446162     1.13   0.256    -.1193299    .4475552
     6#male  |   .1254954   .1048416     1.20   0.231    -.0799904    .3309811
   6#female  |   .1654973   .1443159     1.15   0.251    -.1173567    .4483513
     7#male  |   .1266522   .1045843     1.21   0.226    -.0783294    .3316337
   7#female  |   .1668895   .1440052     1.16   0.246    -.1153555    .4491344
     8#male  |   .1278164   .1043174     1.23   0.220    -.0766419    .3322747
   8#female  |   .1682891   .1436839     1.17   0.242    -.1133262    .4499045
     9#male  |    .128988   .1040407     1.24   0.215    -.0749281    .3329041
   9#female  |   .1696963   .1433523     1.18   0.237    -.1112691    .4506616
    10#male  |    .130167   .1037544     1.25   0.210    -.0731879    .3335218
  10#female  |   .1711109   .1430103     1.20   0.232     -.109184    .4514059
    11#male  |   .1313534   .1034583     1.27   0.204    -.0714212     .334128
  11#female  |   .1725331   .1426578     1.21   0.227    -.1070711    .4521373
    12#male  |   .1325472   .1031526     1.28   0.199    -.0696281    .3347225
  12#female  |   .1739627   .1422951     1.22   0.222    -.1049305    .4528559
    13#male  |   .1337485   .1028371     1.30   0.193    -.0678085    .3353055
  13#female  |   .1753998    .141922     1.24   0.216    -.1027622    .4535617
    14#male  |   .1349571   .1025119     1.32   0.188    -.0659626    .3358769
  14#female  |   .1768443   .1415386     1.25   0.212    -.1005663    .4542549
    15#male  |   .1361733   .1021771     1.33   0.183    -.0640902    .3364367
  15#female  |   .1782964    .141145     1.26   0.207    -.0983428    .4549355
    16#male  |   .1373969   .1018326     1.35   0.177    -.0621914    .3369851
  16#female  |   .1797558   .1407413     1.28   0.202     -.096092    .4556036
    17#male  |   .1386279   .1014785     1.37   0.172    -.0602663    .3375221
  17#female  |   .1812228   .1403274     1.29   0.197    -.0938138    .4562594
    18#male  |   .1398664   .1011147     1.38   0.167    -.0583148    .3380476
  18#female  |   .1826971   .1399034     1.31   0.192    -.0915085    .4569027
    19#male  |   .1411124   .1007414     1.40   0.161    -.0563371    .3385618
  19#female  |   .1841789   .1394694     1.32   0.187     -.089176    .4575339
    20#male  |   .1423658   .1003585     1.42   0.156    -.0543332    .3390648
  20#female  |   .1856682   .1390254     1.34   0.182    -.0868166     .458153
    21#male  |   .1436267    .099966     1.44   0.151    -.0523031    .3395566
  21#female  |   .1871648   .1385715     1.35   0.177    -.0844304    .4587601
    22#male  |   .1448952   .0995641     1.46   0.146     -.050247    .3400373
  22#female  |   .1886689   .1381079     1.37   0.172    -.0820176    .4593553
    23#male  |   .1461711   .0991528     1.47   0.140    -.0481648     .340507
  23#female  |   .1901803   .1376344     1.38   0.167    -.0795782    .4599388
    24#male  |   .1474545   .0987321     1.49   0.135    -.0460568    .3409657
  24#female  |   .1916991   .1371513     1.40   0.162    -.0771125    .4605107
    25#male  |   .1487454    .098302     1.51   0.130     -.043923    .3414137
  25#female  |   .1932253   .1366586     1.41   0.157    -.0746206    .4610712
    26#male  |   .1500438   .0978626     1.53   0.125    -.0417635     .341851
  26#female  |   .1947588   .1361564     1.43   0.153    -.0721028    .4616205
    27#male  |   .1513497   .0974141     1.55   0.120    -.0395784    .3422778
  27#female  |   .1962997   .1356448     1.45   0.148    -.0695591    .4621586
    28#male  |   .1526631   .0969564     1.57   0.115    -.0373679    .3426941
  28#female  |    .197848   .1351238     1.46   0.143    -.0669899    .4626858
    29#male  |    .153984   .0964896     1.60   0.111    -.0351322    .3431002
  29#female  |   .1994035   .1345937     1.48   0.138    -.0643953    .4632023
    30#male  |   .1553125   .0960139     1.62   0.106    -.0328713    .3434962
  30#female  |   .2009663   .1340544     1.50   0.134    -.0617755    .4637082
    31#male  |   .1566484   .0955293     1.64   0.101    -.0305855    .3438823
  31#female  |   .2025365   .1335062     1.52   0.129    -.0591309    .4642039
    32#male  |   .1579919   .0950358     1.66   0.096    -.0282749    .3442586
  32#female  |   .2041139   .1329491     1.54   0.125    -.0564616    .4646894
    33#male  |   .1593428   .0945337     1.69   0.092    -.0259398    .3446254
  33#female  |   .2056986   .1323833     1.55   0.120    -.0537679     .465165
    34#male  |   .1607013    .094023     1.71   0.087    -.0235803    .3449829
  34#female  |   .2072905   .1318088     1.57   0.116    -.0510501     .465631
    35#male  |   .1620673   .0935038     1.73   0.083    -.0211968    .3453313
  35#female  |   .2088896   .1312259     1.59   0.111    -.0483084    .4660876
    36#male  |   .1634408   .0929762     1.76   0.079    -.0187893    .3456708
  36#female  |   .2104959   .1306346     1.61   0.107    -.0455431     .466535
    37#male  |   .1648218   .0924405     1.78   0.075    -.0163582    .3460018
  37#female  |   .2121095   .1300351     1.63   0.103    -.0427547    .4669736
    38#male  |   .1662103   .0918966     1.81   0.071    -.0139038    .3463244
  38#female  |   .2137302   .1294276     1.65   0.099    -.0399433    .4674037
    39#male  |   .1676063   .0913448     1.83   0.067    -.0114263    .3466389
  39#female  |    .215358   .1288122     1.67   0.095    -.0371093    .4678254
    40#male  |   .1690098   .0907853     1.86   0.063    -.0089261    .3469457
  40#female  |    .216993   .1281892     1.69   0.091    -.0342532    .4682392
    41#male  |   .1704208   .0902181     1.89   0.059    -.0064035    .3472451
  41#female  |   .2186351   .1275586     1.71   0.087    -.0313751    .4686453
    42#male  |   .1718393   .0896435     1.92   0.055    -.0038588    .3475373
  42#female  |   .2202843   .1269206     1.74   0.083    -.0284755    .4690442
    43#male  |   .1732653   .0890617     1.95   0.052    -.0012924    .3478229
  43#female  |   .2219406   .1262755     1.76   0.079    -.0255549    .4694361
    44#male  |   .1746987   .0884727     1.97   0.048     .0012953    .3481021
  44#female  |   .2236039   .1256235     1.78   0.075    -.0226136    .4698214
    45#male  |   .1761396    .087877     2.00   0.045     .0039039    .3483753
  45#female  |   .2252742   .1249647     1.80   0.071     -.019652    .4702005
    46#male  |    .177588   .0872746     2.03   0.042      .006533    .3486431
  46#female  |   .2269516   .1242993     1.83   0.068    -.0166707    .4705738
    47#male  |   .1790439   .0866658     2.07   0.039      .009182    .3489057
  47#female  |   .2286359   .1236277     1.85   0.064    -.0136699    .4709417
    48#male  |   .1805072   .0860509     2.10   0.036     .0118506    .3491637
  48#female  |   .2303272     .12295     1.87   0.061    -.0106503    .4713047
    49#male  |   .1819779     .08543     2.13   0.033     .0145382    .3494176
  49#female  |   .2320254   .1222664     1.90   0.058    -.0076123    .4716631
    50#male  |   .1834561   .0848035     2.16   0.031     .0172443     .349668
  50#female  |   .2337305   .1215772     1.92   0.055    -.0045565    .4720175
    51#male  |   .1849417   .0841717     2.20   0.028     .0199682    .3499152
  51#female  |   .2354426   .1208827     1.95   0.051    -.0014833    .4723684
    52#male  |   .1864347   .0835348     2.23   0.026     .0227095      .35016
  52#female  |   .2371614   .1201832     1.97   0.048     .0016067    .4727161
    53#male  |   .1879352   .0828932     2.27   0.023     .0254675    .3504029
  53#female  |   .2388871   .1194788     2.00   0.046     .0047129    .4730614
    54#male  |    .189443   .0822472     2.30   0.021     .0282415    .3506446
  54#female  |   .2406196     .11877     2.03   0.043     .0078347    .4734046
    55#male  |   .1909582   .0815971     2.34   0.019     .0310308    .3508857
  55#female  |   .2423589    .118057     2.05   0.040     .0109715    .4737463
    56#male  |   .1924808   .0809434     2.38   0.017     .0338348    .3511269
  56#female  |   .2441049   .1173401     2.08   0.037     .0141227    .4740872
    57#male  |   .1940108   .0802863     2.42   0.016     .0366525    .3513691
  57#female  |   .2458577   .1166196     2.11   0.035     .0172875    .4744278
    58#male  |   .1955481   .0796263     2.46   0.014     .0394834    .3516129
  58#female  |   .2476171   .1158958     2.14   0.033     .0204655    .4747688
    59#male  |   .1970928   .0789639     2.50   0.013     .0423264    .3518591
  59#female  |   .2493833   .1151692     2.17   0.030     .0236557    .4751108
    60#male  |   .1986448   .0782994     2.54   0.011     .0451807    .3521088
  60#female  |    .251156   .1144401     2.19   0.028     .0268575    .4754545
    61#male  |    .200204   .0776334     2.58   0.010     .0480454    .3523626
  61#female  |   .2529353   .1137088     2.22   0.026     .0300702    .4758005
    62#male  |   .2017706   .0769662     2.62   0.009     .0509196    .3526217
  62#female  |   .2547212   .1129757     2.25   0.024     .0332929    .4761496
    63#male  |   .2033445   .0762986     2.67   0.008      .053802    .3528869
  63#female  |   .2565137   .1122413     2.29   0.022     .0365248    .4765026
    64#male  |   .2049256   .0756309     2.71   0.007     .0566918    .3531594
  64#female  |   .2583126   .1115059     2.32   0.021     .0397652    .4768601
    65#male  |    .206514   .0749637     2.75   0.006     .0595878    .3534402
  65#female  |   .2601181   .1107699     2.35   0.019     .0430131     .477223
    66#male  |   .2081096   .0742977     2.80   0.005     .0624888    .3537304
  66#female  |   .2619299   .1100338     2.38   0.017     .0462677    .4775922
    67#male  |   .2097125   .0736334     2.85   0.004     .0653936    .3540313
  67#female  |   .2637482    .109298     2.41   0.016      .049528    .4779684
    68#male  |   .2113225   .0729716     2.90   0.004     .0683009    .3543441
  68#female  |   .2655729   .1085631     2.45   0.014     .0527932    .4783526
    69#male  |   .2129397   .0723128     2.94   0.003     .0712093    .3546701
  69#female  |   .2674039   .1078294     2.48   0.013     .0560621    .4787456
    70#male  |   .2145641   .0716578     2.99   0.003     .0741174    .3550107
  70#female  |   .2692412   .1070975     2.51   0.012     .0593339    .4791484
    71#male  |   .2161956   .0710073     3.04   0.002     .0770238    .3553674
  71#female  |   .2710847   .1063679     2.55   0.011     .0626075     .479562
    72#male  |   .2178342   .0703621     3.10   0.002      .079927    .3557415
  72#female  |   .2729345   .1056411     2.58   0.010     .0658817    .4799873
    73#male  |     .21948   .0697231     3.15   0.002     .0828252    .3561347
  73#female  |   .2747905   .1049177     2.62   0.009     .0691556    .4804254
    74#male  |   .2211328    .069091     3.20   0.001     .0857169    .3565487
  74#female  |   .2766526   .1041982     2.66   0.008     .0724279    .4808774
    75#male  |   .2227927   .0684667     3.25   0.001     .0886004     .356985
  75#female  |   .2785209   .1034832     2.69   0.007     .0756975    .4813443
    76#male  |   .2244596   .0678512     3.31   0.001     .0914737    .3574454
  76#female  |   .2803952   .1027733     2.73   0.006     .0789632    .4818273
    77#male  |   .2261335   .0672453     3.36   0.001     .0943351    .3579319
  77#female  |   .2822756   .1020691     2.77   0.006     .0822238    .4823275
    78#male  |   .2278145   .0666501     3.42   0.001     .0971827    .3584462
  78#female  |    .284162   .1013713     2.80   0.005      .085478    .4828461
    79#male  |   .2295024   .0660666     3.47   0.001     .1000143    .3589904
  79#female  |   .2860544   .1006804     2.84   0.004     .0887244    .4833843
    80#male  |   .2311972   .0654957     3.53   0.000     .1028279    .3595665
  80#female  |   .2879526   .0999971     2.88   0.004     .0919618    .4839434
    81#male  |    .232899   .0649387     3.59   0.000     .1056214    .3601765
  81#female  |   .2898568   .0993222     2.92   0.004     .0951889    .4845247
    82#male  |   .2346076   .0643966     3.64   0.000     .1083926    .3608226
  82#female  |   .2917668   .0986563     2.96   0.003     .0984041    .4851295
    83#male  |   .2363232   .0638706     3.70   0.000     .1111392    .3615072
  83#female  |   .2936826       .098     3.00   0.003     .1016061    .4857591
    84#male  |   .2380455   .0633618     3.76   0.000     .1138588    .3622323
  84#female  |   .2956042   .0973542     3.04   0.002     .1047934    .4864149
    85#male  |   .2397747   .0628714     3.81   0.000      .116549    .3630004
  85#female  |   .2975314   .0967196     3.08   0.002     .1079645    .4870984
    86#male  |   .2415107   .0624007     3.87   0.000     .1192075    .3638139
  86#female  |   .2994644   .0960969     3.12   0.002     .1111179    .4878108
    87#male  |   .2432535    .061951     3.93   0.000     .1218318    .3646751
  87#female  |   .3014029   .0954869     3.16   0.002     .1142521    .4885538
    88#male  |   .2450029   .0615234     3.98   0.000     .1244193    .3655866
  88#female  |   .3033471   .0948904     3.20   0.001     .1173654    .4893288
    89#male  |   .2467591   .0611193     4.04   0.000     .1269674    .3665508
  89#female  |   .3052968   .0943081     3.24   0.001     .1204562    .4901373
    90#male  |    .248522     .06074     4.09   0.000     .1294737    .3675703
  90#female  |    .307252    .093741     3.28   0.001      .123523    .4909809
    91#male  |   .2502915   .0603868     4.14   0.000     .1319356    .3686474
  91#female  |   .3092126   .0931897     3.32   0.001     .1265642     .491861
    92#male  |   .2520676   .0600609     4.20   0.000     .1343504    .3697849
  92#female  |   .3111786   .0926551     3.36   0.001     .1295779    .4927794
    93#male  |   .2538503   .0597637     4.25   0.000     .1367156     .370985
  93#female  |     .31315   .0921381     3.40   0.001     .1325626    .4937374
    94#male  |   .2556396   .0594964     4.30   0.000     .1390288    .3722504
  94#female  |   .3151267   .0916395     3.44   0.001     .1355166    .4947368
    95#male  |   .2574354   .0592603     4.34   0.000     .1412874    .3735835
  95#female  |   .3171087   .0911601     3.48   0.001     .1384382    .4957792
    96#male  |   .2592377   .0590566     4.39   0.000     .1434889    .3749865
  96#female  |   .3190959   .0907007     3.52   0.000     .1413257    .4968661
    97#male  |   .2610464   .0588865     4.43   0.000     .1456311    .3764618
  97#female  |   .3210882   .0902623     3.56   0.000     .1441774    .4979991
    98#male  |   .2628616   .0587511     4.47   0.000     .1477116    .3780116
  98#female  |   .3230857   .0898456     3.60   0.000     .1469915    .4991799
    99#male  |   .2646831   .0586515     4.51   0.000     .1497282    .3796381
  99#female  |   .3250882   .0894515     3.63   0.000     .1497664      .50041
   100#male  |    .266511   .0585889     4.55   0.000      .151679    .3813431
 100#female  |   .3270958   .0890809     3.67   0.000     .1525005     .501691
   101#male  |   .2683453    .058564     4.58   0.000     .1535619    .3831286
 101#female  |   .3291083   .0887344     3.71   0.000      .155192    .5030245
   102#male  |   .2701858   .0585779     4.61   0.000     .1553753    .3849963
 102#female  |   .3311257    .088413     3.75   0.000     .1578394     .504412
   103#male  |   .2720325   .0586313     4.64   0.000     .1571174    .3869477
 103#female  |    .333148   .0881175     3.78   0.000      .160441    .5058551
   104#male  |   .2738855    .058725     4.66   0.000     .1587867    .3889843
 104#female  |   .3351751   .0878485     3.82   0.000     .1629952     .507355
   105#male  |   .2757447   .0588595     4.68   0.000     .1603821    .3911072
 105#female  |    .337207   .0876069     3.85   0.000     .1655006    .5089134
   106#male  |   .2776099   .0590356     4.70   0.000     .1619024    .3933175
 106#female  |   .3392436   .0873934     3.88   0.000     .1679556    .5105316
   107#male  |   .2794813   .0592535     4.72   0.000     .1633466    .3956161
 107#female  |   .3412848   .0872088     3.91   0.000     .1703588    .5122109
   108#male  |   .2813588   .0595137     4.73   0.000     .1647141    .3980035
 108#female  |   .3433307   .0870535     3.94   0.000     .1727089    .5139525
   109#male  |   .2832423   .0598164     4.74   0.000     .1660043    .4004802
 109#female  |   .3453811   .0869284     3.97   0.000     .1750045    .5157578
   110#male  |   .2851317   .0601617     4.74   0.000      .167217    .4030465
 110#female  |   .3474361   .0868341     4.00   0.000     .1772444    .5176277
   111#male  |   .2870271   .0605497     4.74   0.000     .1683519    .4057023
 111#female  |   .3494954    .086771     4.03   0.000     .1794274    .5195634
   112#male  |   .2889284   .0609803     4.74   0.000     .1694091    .4084477
 112#female  |   .3515592   .0867398     4.05   0.000     .1815524     .521566
   113#male  |   .2908356   .0614535     4.73   0.000     .1703889    .4112822
 113#female  |   .3536272   .0867408     4.08   0.000     .1836184    .5236361
   114#male  |   .2927485   .0619689     4.72   0.000     .1712918    .4142053
 114#female  |   .3556996   .0867746     4.10   0.000     .1856244    .5257748
   115#male  |   .2946673   .0625262     4.71   0.000     .1721181    .4172164
 115#female  |   .3577762   .0868416     4.12   0.000     .1875697    .5279827
   116#male  |   .2965918   .0631251     4.70   0.000     .1728688    .4203147
 116#female  |    .359857   .0869421     4.14   0.000     .1894536    .5302604
   117#male  |    .298522    .063765     4.68   0.000     .1735448    .4234992
 117#female  |   .3619418   .0870764     4.16   0.000     .1912752    .5326084
   118#male  |   .3004578   .0644455     4.66   0.000     .1741469    .4267687
 118#female  |   .3640308   .0872447     4.17   0.000     .1930343    .5350273
   119#male  |   .3023992   .0651659     4.64   0.000     .1746765     .430122
 119#female  |   .3661237   .0874473     4.19   0.000     .1947301    .5375172
   120#male  |   .3043462   .0659255     4.62   0.000     .1751346    .4335579
 120#female  |   .3682206   .0876843     4.20   0.000     .1963626    .5400786
   121#male  |   .3062988   .0667237     4.59   0.000     .1755228    .4370748
 121#female  |   .3703213   .0879557     4.21   0.000     .1979313    .5427114
   122#male  |   .3082567   .0675596     4.56   0.000     .1758423    .4406712
 122#female  |   .3724259   .0882617     4.22   0.000     .1994361    .5454157
   123#male  |   .3102202   .0684326     4.53   0.000     .1760948    .4443455
 123#female  |   .3745343   .0886022     4.23   0.000     .2008771    .5481914
   124#male  |   .3121889   .0693417     4.50   0.000     .1762818    .4480961
 124#female  |   .3766463   .0889772     4.23   0.000     .2022543    .5510384
   125#male  |   .3141631   .0702861     4.47   0.000     .1764048    .4519213
 125#female  |    .378762   .0893865     4.24   0.000     .2035678    .5539563
   126#male  |   .3161425    .071265     4.44   0.000     .1764656    .4558194
 126#female  |   .3808813     .08983     4.24   0.000     .2048179    .5569448
   127#male  |   .3181271   .0722775     4.40   0.000     .1764657    .4597885
 127#female  |   .3830042   .0903074     4.24   0.000     .2060049    .5600034
   128#male  |   .3201169   .0733228     4.37   0.000      .176407    .4638269
 128#female  |   .3851305   .0908186     4.24   0.000     .2071293    .5631316
   129#male  |   .3221119   .0743998     4.33   0.000      .176291    .4679328
 129#female  |   .3872602   .0913632     4.24   0.000     .2081916    .5663288
   130#male  |    .324112   .0755077     4.29   0.000     .1761195    .4721044
 130#female  |   .3893932   .0919409     4.24   0.000     .2091923    .5695941
   131#male  |   .3261171   .0766457     4.25   0.000     .1758943    .4763399
 131#female  |   .3915296   .0925513     4.23   0.000     .2101323    .5729269
   132#male  |   .3281272   .0778128     4.22   0.000     .1756168    .4806375
 132#female  |   .3936691   .0931941     4.22   0.000     .2110121    .5763262
   133#male  |   .3301422   .0790083     4.18   0.000     .1752889    .4849956
 133#female  |   .3958119   .0938687     4.22   0.000     .2118327    .5797911
   134#male  |   .3321622   .0802311     4.14   0.000     .1749122    .4894122
 134#female  |   .3979577   .0945746     4.21   0.000     .2125949    .5833206
   135#male  |    .334187   .0814804     4.10   0.000     .1744883    .4938857
 135#female  |   .4001066   .0953115     4.20   0.000     .2132996    .5869136
   136#male  |   .3362165   .0827555     4.06   0.000     .1740187    .4984143
 136#female  |   .4022585   .0960786     4.19   0.000     .2139478    .5905691
   137#male  |   .3382508   .0840555     4.02   0.000     .1735051    .5029965
 137#female  |   .4044132   .0968756     4.17   0.000     .2145406    .5942859
   138#male  |   .3402898   .0853795     3.99   0.000      .172949    .5076306
 138#female  |   .4065709   .0977017     4.16   0.000      .215079    .5980627
   139#male  |   .3423334   .0867269     3.95   0.000     .1723519     .512315
 139#female  |   .4087313   .0985565     4.15   0.000     .2155642    .6018984
   140#male  |   .3443816   .0880967     3.91   0.000     .1717152     .517048
 140#female  |   .4108944   .0994392     4.13   0.000     .2159972    .6057917
   141#male  |   .3464344   .0894884     3.87   0.000     .1710404    .5218283
 141#female  |   .4130603   .1003493     4.12   0.000     .2163793    .6097412
   142#male  |   .3484916    .090901     3.83   0.000     .1703288    .5266543
 142#female  |   .4152287   .1012861     4.10   0.000     .2167116    .6137457
   143#male  |   .3505532    .092334     3.80   0.000     .1695819    .5315244
 143#female  |   .4173996   .1022489     4.08   0.000     .2169954    .6178038
   144#male  |   .3526192   .0937866     3.76   0.000     .1688009    .5364374
 144#female  |    .419573   .1032371     4.06   0.000     .2172319    .6219141
   145#male  |   .3546895   .0952581     3.72   0.000      .167987    .5413919
 145#female  |   .4217489   .1042501     4.05   0.000     .2174223    .6260754
   146#male  |    .356764   .0967479     3.69   0.000     .1671416    .5463864
 146#female  |    .423927   .1052872     4.03   0.000     .2175679    .6302861
   147#male  |   .3588427   .0982553     3.65   0.000     .1662659    .5514196
 147#female  |   .4261074   .1063476     4.01   0.000       .21767    .6345449
   148#male  |   .3609256   .0997797     3.62   0.000      .165361    .5564902
 148#female  |   .4282901   .1074308     3.99   0.000     .2177297    .6388505
   149#male  |   .3630126   .1013205     3.58   0.000     .1644281    .5615971
 149#female  |   .4304749   .1085359     3.97   0.000     .2177483    .6432014
   150#male  |   .3651036   .1028771     3.55   0.000     .1634682    .5667389
 150#female  |   .4326618   .1096625     3.95   0.000     .2177272    .6475963
   151#male  |   .3671985   .1044489     3.52   0.000     .1624825    .5719145
 151#female  |   .4348506   .1108098     3.92   0.000     .2176675    .6520338
------------------------------------------------------------------------------

. marginsplot, ///
> scheme(s1mono) graphregion(fcolor(white) ilcolor(white) lcolor(white))

  Variables that uniquely identify margins: att sex

. 
. 
. 
end of do-file

. log close
      name:  <unnamed>
       log:  /Users/bundi/Desktop/Self-Selection and Misreporting/Revision/Repl
> ication/Replication_Final/pep_session_replication.smcl
  log type:  smcl
 closed on:  15 Jul 2016, 14:29:07
-------------------------------------------------------------------------------
